class Network(nn.Module):
    ...
    def __init__(self):
        self.criterion = CTCLoss()

data size before warp ctc
torch.Size([82, 16, 34]) torch.Size([35]) torch.Size([16]) torch.Size([16]) 

data size before warp ctc
torch.Size([82, 16, 34]) torch.Size([35]) torch.Size([16]) torch.Size([16]) 
Traceback (most recent call last):
  File "train.py", line 473, in <module>
    train()
  File "train.py", line 300, in train
    target_det=target_det, target_ctc=target_ctc, target_sizes=target_sizes)
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 491, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 115, in forward
    return self.gather(outputs, self.output_device)
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 127, in gather
    return gather(outputs, output_device, dim=self.dim)
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/parallel/scatter_gather.py", line 68, in gather
    return gather_map(outputs)
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/parallel/scatter_gather.py", line 63, in gather_map
    return type(out)(map(gather_map, zip(*outputs)))
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/parallel/scatter_gather.py", line 55, in gather_map
    return Gather.apply(target_device, dim, *outputs)
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/parallel/_functions.py", line 54, in forward
    ctx.input_sizes = tuple(map(lambda i: i.size(ctx.dim), inputs))
  File "/home/charlie_huang/virtual3/lib/python3.5/site-packages/torch/nn/parallel/_functions.py", line 54, in <lambda>
    ctx.input_sizes = tuple(map(lambda i: i.size(ctx.dim), inputs))
RuntimeError: dimension specified as 0 but tensor has no dimensions

Traceback (most recent call last):
  File "train.py", line 343, in <module>
    loss.backward()
  File "/home/jbaik/.pyenv/versions/3.6.4/lib/python3.6/site-packages/torch/autograd/variable.py", line 128, in backward
    torch.autograd.backward(self, gradient, retain_graph, create_graph)
  File "/home/jbaik/.pyenv/versions/3.6.4/lib/python3.6/site-packages/torch/autograd/__init__.py", line 83, in backward
    variables, grad_variables, retain_graph, create_graph)
RuntimeError: expected Variable (got 'torch.cuda.FloatTensor')'

cmake ../ 

-- The C compiler identification is AppleClang 9.0.0.9000039
-- The CXX compiler identification is AppleClang 9.0.0.9000039
-- Check for working C compiler: /Library/Developer/CommandLineTools/usr/bin/cc
-- Check for working C compiler: /Library/Developer/CommandLineTools/usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /Library/Developer/CommandLineTools/usr/bin/c++
-- Check for working CXX compiler: /Library/Developer/CommandLineTools/usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
CUDA_TOOLKIT_ROOT_DIR not found or specified
-- Could NOT find CUDA (missing: CUDA_TOOLKIT_ROOT_DIR CUDA_NVCC_EXECUTABLE CUDA_INCLUDE_DIRS CUDA_CUDART_LIBRARY) (Required is at least version "6.5")
-- cuda found FALSE
CMake Warning at CMakeLists.txt:59 (FIND_PACKAGE):
  By not providing "FindTorch.cmake" in CMAKE_MODULE_PATH this project has
  asked CMake to find a package configuration file provided by "Torch", but
  CMake did not find one.

  Could not find a package configuration file provided by "Torch" with any of
  the following names:

    TorchConfig.cmake
    torch-config.cmake

  Add the installation prefix of "Torch" to CMAKE_PREFIX_PATH or set
  "Torch_DIR" to a directory containing one of the above files.  If "Torch"
  provides a separate development package or SDK, be sure it has been
  installed.


-- Torch found Torch_DIR-NOTFOUND
-- DARWIN_VERSION=17
-- Building shared library with no GPU support
-- Configuring done
-- Generating done
-- Build files have been written to: /Users/cdong/projects/python/warp-ctc/build

make

clang: error: unsupported option '-fopenmp'
make[2]: *** [CMakeFiles/warpctc.dir/src/ctc_entrypoint.cpp.o] Error 1
make[1]: *** [CMakeFiles/warpctc.dir/all] Error 2
make: *** [all] Error 2

from ._warp_ctc import lib

Traceback (most recent call last):
  File "test.py", line 8, in <module>
    from warpctc_pytorch import CTCLoss
  File "/usr/local/lib/python3.4/dist-packages/warpctc_pytorch/__init__.py", line 8, in <module>
    from ._warp_ctc import lib as _lib, ffi as _ffi
ImportError: /usr/local/lib/python3.4/dist-packages/warpctc_pytorch/_warp_ctc.cpython-34m.so: undefined symbol: _Z7cpu_ctcP13THFloatTensorS0_P11THIntTensorS2_S2_iS0_

!cmake ..
!make
/bin/sh: 1: cmake: not found
make: *** No targets specified and no makefile found.  Stop.

-- The C compiler identification is AppleClang 9.0.0.9000039
-- The CXX compiler identification is AppleClang 9.0.0.9000039
-- Check for working C compiler: /Library/Developer/CommandLineTools/usr/bin/cc
-- Check for working C compiler: /Library/Developer/CommandLineTools/usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /Library/Developer/CommandLineTools/usr/bin/c++
-- Check for working CXX compiler: /Library/Developer/CommandLineTools/usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
CUDA_TOOLKIT_ROOT_DIR not found or specified
-- Could NOT find CUDA (missing: CUDA_TOOLKIT_ROOT_DIR CUDA_NVCC_EXECUTABLE CUDA_INCLUDE_DIRS CUDA_CUDART_LIBRARY) (Required is at least version "6.5")
-- cuda found FALSE
CMake Warning at CMakeLists.txt:59 (FIND_PACKAGE):
  By not providing "FindTorch.cmake" in CMAKE_MODULE_PATH this project has
  asked CMake to find a package configuration file provided by "Torch", but
  CMake did not find one.

  Could not find a package configuration file provided by "Torch" with any of
  the following names:

    TorchConfig.cmake
    torch-config.cmake

  Add the installation prefix of "Torch" to CMAKE_PREFIX_PATH or set
  "Torch_DIR" to a directory containing one of the above files.  If "Torch"
  provides a separate development package or SDK, be sure it has been
  installed.


-- Torch found Torch_DIR-NOTFOUND
-- DARWIN_VERSION=17
-- Building shared library with no GPU support
-- Configuring done
-- Generating done
-- Build files have been written to: /Users/cdong/projects/python/warp-ctc/build

Scanning dependencies of target warpctc
[ 25%] Building CXX object CMakeFiles/warpctc.dir/src/ctc_entrypoint.cpp.o
[ 50%] Linking CXX shared library libwarpctc.dylib
[ 50%] Built target warpctc
Scanning dependencies of target test_cpu
[ 75%] Building CXX object CMakeFiles/test_cpu.dir/tests/test_cpu.cpp.o
[100%] Linking CXX executable test_cpu
[100%] Built target test_cpu

cd ../pytorch_binding/
python setup.py install

CUDA_HOME not found in the environment so building without GPU support. To build with GPU support please define the CUDA_HOME environment variable. This should be a path which contains include/cuda.h
generating build/_warp_ctc.c
regenerated: 'build/_warp_ctc.c'
running install
running build
running build_py
creating build/lib.macosx-10.6-x86_64-3.5
creating build/lib.macosx-10.6-x86_64-3.5/warpctc_pytorch
copying warpctc_pytorch/__init__.py -> build/lib.macosx-10.6-x86_64-3.5/warpctc_pytorch
running build_ext
building 'warpctc_pytorch._warp_ctc' extension
creating build/temp.macosx-10.6-x86_64-3.5
creating build/temp.macosx-10.6-x86_64-3.5/build
creating build/temp.macosx-10.6-x86_64-3.5/Users
creating build/temp.macosx-10.6-x86_64-3.5/Users/cdong
creating build/temp.macosx-10.6-x86_64-3.5/Users/cdong/projects
creating build/temp.macosx-10.6-x86_64-3.5/Users/cdong/projects/python
creating build/temp.macosx-10.6-x86_64-3.5/Users/cdong/projects/python/warp-ctc
creating build/temp.macosx-10.6-x86_64-3.5/Users/cdong/projects/python/warp-ctc/pytorch_binding
creating build/temp.macosx-10.6-x86_64-3.5/Users/cdong/projects/python/warp-ctc/pytorch_binding/src
/usr/bin/clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/cdong/projects/python/dnn-model-ocr/envs/default/include -arch x86_64 -I/Users/cdong/projects/python/dnn-model-ocr/envs/default/include -arch x86_64 -I/Users/cdong/projects/python/dnn-model-ocr/envs/default/lib/python3.5/site-packages/torch/utils/ffi/../../lib/include -I/Users/cdong/projects/python/dnn-model-ocr/envs/default/lib/python3.5/site-packages/torch/utils/ffi/../../lib/include/TH -I/Users/cdong/projects/python/warp-ctc/include -I/Users/cdong/projects/python/dnn-model-ocr/envs/default/include/python3.5m -c build/_warp_ctc.c -o build/temp.macosx-10.6-x86_64-3.5/build/_warp_ctc.o -std=c++11 -fPIC
error: invalid argument '-std=c++11' not allowed with 'C/ObjC'
error: command '/usr/bin/clang' failed with exit status 1

#encoding:utf8
import os
import sys
import torch
import warpctc_pytorch
import traceback

import torchvision
from torch import nn, autograd, FloatTensor, optim
from torch.nn import functional as F
from torch.utils.data import DataLoader
from torch.optim.lr_scheduler import MultiStepLR
from tensorboard import SummaryWriter
from pprint import pprint

from net.utils import decoder

from logging import getLogger, StreamHandler
logger = getLogger(__name__)
handler = StreamHandler(sys.stdout)
logger.addHandler(handler)

from dataset_util.utils import id_to_character
from dataset_util.transform import rescale, normalizer
from config.config import MAX_CAPTCHA_LENGTH, TENSORBOARD_LOG_PATH, MODEL_PATH


class CNN_RNN(nn.Module):
    def __init__(self, lstm_bidirectional=True, use_ctc=True, *args, **kwargs):
        super(CNN_RNN, self).__init__(*args, **kwargs)
        model_conv = torchvision.models.resnet18(pretrained=True)
        # for param in model_conv.parameters():
        #     param.requires_grad = False
        #
        modules = list(model_conv.children())[:-1]  # delete the last fc layer.
        # for param in modules[8].parameters():
        #     param.requires_grad = True

        self.resnet = nn.Sequential(*modules)            # CNN with fixed parameters from resnet as feature extractor
        self.lstm_input_size = 512 * 2 * 2
        self.lstm_hidden_state_size = 512
        self.lstm_num_layers = 2
        self.chracter_space_length = 64
        self._lstm_bidirectional = lstm_bidirectional
        self._use_ctc = use_ctc
        if use_ctc:
            # self._max_captcha_length = int(MAX_CAPTCHA_LENGTH * 2)
            self._max_captcha_length = 8
        else:
            self._max_captcha_length = MAX_CAPTCHA_LENGTH

        if lstm_bidirectional:
            self.lstm_hidden_state_size = self.lstm_hidden_state_size * 2           # so that hidden size for one direction in bidirection lstm is the same as vanilla lstm
            self.lstm = self.lstm = nn.LSTM(self.lstm_input_size, self.lstm_hidden_state_size // 2, dropout=0.5, bidirectional=True, num_layers=self.lstm_num_layers)
        else:
            self.lstm = nn.LSTM(self.lstm_input_size, self.lstm_hidden_state_size, dropout=0.5, bidirectional=False, num_layers=self.lstm_num_layers)  # dropout doen't work for one layer lstm

        self.ouput_to_tag = nn.Linear(self.lstm_hidden_state_size, self.chracter_space_length)
        # self.dropout_lstm = nn.Dropout()


    def init_hidden_status(self, batch_size):
        if self._lstm_bidirectional:
            self.hidden = (autograd.Variable(torch.zeros((self.lstm_num_layers * 2, batch_size, self.lstm_hidden_state_size // 2))),
                           autograd.Variable(torch.zeros((self.lstm_num_layers * 2, batch_size, self.lstm_hidden_state_size // 2)))) # number of layers, batch size, hidden dimention
        else:
            self.hidden = (autograd.Variable(torch.zeros((self.lstm_num_layers, batch_size, self.lstm_hidden_state_size))),
                           autograd.Variable(torch.zeros((self.lstm_num_layers, batch_size, self.lstm_hidden_state_size)))) # number of layers, batch size, hidden dimention


    def forward(self, image):
        '''
        :param image:  # batch_size, CHANNEL, HEIGHT, WIDTH
        :return:
        '''
        features = self.resnet(image)                 # [batch_size, 512, 2, 2]
        batch_size = image.shape[0]
        features = [features.view(batch_size, -1) for i in range(self._max_captcha_length)]
        features = torch.stack(features)
        self.init_hidden_status(batch_size)
        output, hidden = self.lstm(features, self.hidden)
        # output = self.dropout_lstm(output)
        tag_space = self.ouput_to_tag(output.view(-1, output.size(2)))      # [MAX_CAPTCHA_LENGTH * BATCH_SIZE, CHARACTER_SPACE_LENGTH]
        tag_space = tag_space.view(self._max_captcha_length, batch_size, -1)

        if not self._use_ctc:
            tag_score = F.log_softmax(tag_space, dim=2)             # [MAX_CAPTCHA_LENGTH, BATCH_SIZE, CHARACTER_SPACE_LENGTH]
        else:
            tag_score = tag_space

        return tag_score


    def save_model(self, model_path):
        torch.save(self, model_path)


    @classmethod
    def load_model(cls, model_path=MODEL_PATH, *args, **kwargs):
        if os.path.exists(model_path):
            model = torch.load(model_path)
            net = model
        else:
            net = cls(*args, **kwargs)

        return net



class Trainer(object):
    def __init__(self, model, use_ctc=True):
        self.model = model
        self._use_ctc = use_ctc
        self.tensorboard_writer = SummaryWriter(TENSORBOARD_LOG_PATH)


    def __del__(self):
        if self.tensorboard_writer:
            self.tensorboard_writer.close()


    def train_net(self, data_loader, eval_data_loader=None, learning_rate=0.008, epoch_num=400):
        try:
            if self._use_ctc:
                loss_function = warpctc_pytorch.warp_ctc.CTCLoss()
            else:
                loss_function = nn.NLLLoss()

            # optimizer = optim.SGD(filter(lambda p: p.requires_grad, self.model.parameters()), momentum=0.2, lr=learning_rate)
            # optimizer = optim.RMSprop(filter(lambda p: p.requires_grad, self.model.parameters()), lr=learning_rate)
            # optimizer = MultiStepLR(optimizer, milestones=[10,15], gamma=0.5)
            optimizer = optim.Adagrad(filter(lambda p: p.requires_grad, self.model.parameters()))

            # optimizer = optim.Adadelta(filter(lambda p: p.requires_grad, self.parameters()))
            # optimizer = optim.Adam(filter(lambda p: p.requires_grad, self.model.parameters()))
            self.tensorboard_writer.add_scalar("learning_rate", learning_rate)

            tensorbard_global_step=0
            if os.path.exists(os.path.join(TENSORBOARD_LOG_PATH, "resume_step")):
                with open(os.path.join(TENSORBOARD_LOG_PATH, "resume_step"), "r") as file_handler:
                    tensorbard_global_step = int(file_handler.read()) + 1

            for epoch_index, epoch in enumerate(range(epoch_num)):
                for index, sample in enumerate(data_loader):
                    optimizer.zero_grad()
                    input_image = autograd.Variable(sample["image"])        # batch_size, 3, 255, 255
                    tag_score = self.model.forward(input_image)

                    if self._use_ctc:
                        tag_score, target, tag_score_sizes, target_sizes = self._loss_preprocess_ctc(tag_score, sample)
                        loss = loss_function(tag_score, target, tag_score_sizes, target_sizes)
                        loss = loss / tag_score.size(1) / self.model._max_captcha_length

                    else:
                        target = sample["padded_label_idx"]
                        tag_score, target = self._loss_preprocess(tag_score, target)
                        loss = loss_function(tag_score, target)

                    print("Training loss: {}".format(float(loss)))
                    self.tensorboard_writer.add_scalar("training_loss", float(loss), tensorbard_global_step)
                    loss.backward()

                    # torch.nn.utils.clip_grad_norm(self.model.lstm.parameters(), 0.5)
                    # for param_index, parameter in enumerate(self.model.lstm.parameters()):
                    #     parameter_sqrt_square_mean = torch.mean(torch.sqrt(torch.mul(parameter, parameter)))
                    #     self.tensorboard_writer.add_scalar("lstm_grad_mean_{}".format(param_index), float(parameter_sqrt_square_mean), tensorbard_global_step)

                    optimizer.step()

                    if index % 250 == 0:
                        print(u"Processing batch: {} of {}, epoch: {}".format(index, len(data_loader), epoch_index))
                        self.evaluate(eval_data_loader, loss_function, tensorbard_global_step)

                    tensorbard_global_step += 1

                self.model.save_model(MODEL_PATH + "_epoch_{}".format(epoch_index))

        except KeyboardInterrupt:
            print("Exit for KeyboardInterrupt, save model")
            self.model.save_model(MODEL_PATH)

            with open(os.path.join(TENSORBOARD_LOG_PATH, "resume_step"), "w") as file_handler:
                file_handler.write(str(tensorbard_global_step))

        except Exception as excp:
            logger.error(str(excp))
            logger.error(traceback.format_exc())


    def predict(self, image):
        # TODO ctc version
        '''
        :param image: [batch_size, channel, height, width]
        :return:
        '''
        tag_score = self.model.forward(image)
        # TODO ctc
        # if self._use_ctc:
        #     tag_score = F.softmax(tag_score, dim=-1)
        #     decoder.decode(tag_score)

        confidence_log_probability, indexes = tag_score.max(2)

        predicted_labels = []
        for batch_index in range(indexes.size(1)):
            label = ""
            for character_index in range(self.model._max_captcha_length):
                if int(indexes[character_index, batch_index]) != 1:
                    label += id_to_character[int(indexes[character_index, batch_index])]
            predicted_labels.append(label)

        return predicted_labels, tag_score


    def predict_pil_image(self, pil_image):
        try:
            self.model.eval()
            processed_image = normalizer(rescale({"image": pil_image}))["image"].view(1, 3, 255, 255)
            result, tag_score = self.predict(processed_image)
            self.model.train()

        except Exception as excp:
            logger.error(str(excp))
            logger.error(traceback.format_exc())
            return [""], None

        return result, tag_score


    def evaluate(self, eval_dataloader, loss_function, step=0):
        total = 0
        sequence_correct = 0
        character_correct = 0
        character_total = 0
        loss_total = 0
        batch_size = eval_data_loader.batch_size
        true_predicted = {}
        self.model.eval()
        for sample in eval_dataloader:
            total += batch_size
            input_images = sample["image"]
            predicted_labels, tag_score = self.predict(input_images)

            for predicted, true_label in zip(predicted_labels, sample["label"]):
                if predicted == true_label:                  # dataloader is making label a list, use batch_size=1
                    sequence_correct += 1

                for index, true_character in enumerate(true_label):
                    character_total += 1
                    if index < len(predicted) and predicted[index] == true_character:
                        character_correct += 1

                true_predicted[true_label] = predicted

            if self._use_ctc:
                tag_score, target, tag_score_sizes, target_sizes = self._loss_preprocess_ctc(tag_score, sample)
                loss_total += float(loss_function(tag_score, target, tag_score_sizes, target_sizes) / batch_size / self.model._max_captcha_length)

            else:
                tag_score, target = self._loss_preprocess(tag_score, sample["padded_label_idx"])
                loss_total += float(loss_function(tag_score, target))  # averaged over batch index

        print("True captcha to predicted captcha: ")
        pprint(true_predicted)
        self.tensorboard_writer.add_text("eval_ture_to_predicted", str(true_predicted), global_step=step)

        accuracy = float(sequence_correct) / total
        avg_loss = float(loss_total) / (total / batch_size)
        character_accuracy = float(character_correct) / character_total
        self.tensorboard_writer.add_scalar("eval_sequence_accuracy", accuracy, global_step=step)
        self.tensorboard_writer.add_scalar("eval_character_accuracy", character_accuracy, global_step=step)
        self.tensorboard_writer.add_scalar("eval_loss", avg_loss, global_step=step)
        self.model.train()


    def _loss_preprocess(self, tag_score, target):
        '''
        :param tag_score:  value return by self.forward
        :param target:     sample["padded_label_idx"]
        :return:           (processed_tag_score, processed_target)  ready for NLLoss function
        '''
        target = target.transpose(0, 1)
        target = target.contiguous()
        target = target.view(target.size(0) * target.size(1))
        tag_score = tag_score.view(-1, self.model.chracter_space_length)

        return tag_score, target


    def _loss_preprocess_ctc(self, tag_score, sample):
        target_2d = [
            [int(ele) for ele in sample["padded_label_idx"][row, :] if int(ele) != 0 and int(ele) != 1]
            for row in range(sample["padded_label_idx"].size(0))]
        target = []
        for ele in target_2d:
            target.extend(ele)
        target = autograd.Variable(torch.IntTensor(target))

        # tag_score = F.softmax(F.sigmoid(tag_score), dim=-1)
        tag_score_sizes = autograd.Variable(torch.IntTensor([self.model._max_captcha_length] * tag_score.size(1)))
        target_sizes = autograd.Variable(sample["captcha_length"].int())

        return tag_score, target, tag_score_sizes, target_sizes


if __name__ == "__main__":
    from dataset_util.dataset import dataset, eval_dataset
    data_loader = DataLoader(dataset, batch_size=3, shuffle=True)
    eval_data_loader = DataLoader(eval_dataset, batch_size=3, shuffle=True)

    net = CNN_RNN.load_model(model_path=MODEL_PATH, lstm_bidirectional=True, use_ctc=True)
    trainer = Trainer(model=net, use_ctc=True)

    trainer.train_net(data_loader, eval_data_loader=eval_data_loader)
    # net.predict(dataset[0]["image"].view(1, 3, 255, 255))

    # predict_pil_image test code
    # from config.config import IMAGE_PATHS
    # import glob
    # from PIL import Image
    #
    # image_paths = glob.glob(os.path.join(IMAGE_PATHS.get("EVAL"), "*.png"))
    # for image_path in image_paths:
    #     pil_image = Image.open(image_path)
    #     predicted, score = net.predict_pil_image(pil_image)
    #     print("True value: {}, predicted: {}".format(os.path.split(image_path)[1], predicted))

    print("Done")

$ python setup.py install
generating build/warpctc_pytorch/_warp_ctc/__warp_ctc.c
(already up-to-date)
not modified: 'build/warpctc_pytorch/_warp_ctc/__warp_ctc.c'
running install
running bdist_egg
running egg_info
writing warpctc_pytorch.egg-info/PKG-INFO
writing dependency_links to warpctc_pytorch.egg-info/dependency_links.txt
writing top-level names to warpctc_pytorch.egg-info/top_level.txt
reading manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
writing manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
installing library code to build/bdist.linux-x86_64/egg
running install_lib
running build_py
copying warpctc_pytorch/_warp_ctc/__init__.py -> build/lib.linux-x86_64-3.6/warpctc_pytorch/_warp_ctc
running build_ext
building 'warpctc_pytorch._warp_ctc.__warp_ctc' extension
gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include -I/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH -I/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/home/jbaik/setup/pytorch/sn.warp-ctc/include -I/home/jbaik/.pyenv/versions/3.6.5/include/python3.6m -c build/warpctc_pytorch/_warp_ctc/__warp_ctc.c -o build/temp.linux-x86_64-3.6/build/warpctc_pytorch/_warp_ctc/__warp_ctc.o -std=c99 -std=c++11 -fPIC -DWARPCTC_ENABLE_GPU
cc1: warning: command line option ‘-std=c++11’ is valid for C++/ObjC++ but not for C [enabled by default]
gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include -I/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH -I/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/home/jbaik/setup/pytorch/sn.warp-ctc/include -I/home/jbaik/.pyenv/versions/3.6.5/include/python3.6m -c /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp -o build/temp.linux-x86_64-3.6/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.o -std=c99 -std=c++11 -fPIC -DWARPCTC_ENABLE_GPU
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++ [enabled by default]
cc1plus: warning: command line option ‘-std=c99’ is valid for C/ObjC but not for C++ [enabled by default]
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp: In function ‘int cpu_ctc(THTensor*, THTensor*, THTensor*, THTensor*, THTensor*, int, THTensor*)’:
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:25:29: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     float *probs_ptr = probs->storage->data + probs->storageOffset;
                             ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:25:52: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     float *probs_ptr = probs->storage->data + probs->storageOffset;
                                                    ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:27:14: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     if (grads->storage) {
              ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:28:30: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
             grads_ptr = grads->storage->data + grads->storageOffset;
                              ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:28:53: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
             grads_ptr = grads->storage->data + grads->storageOffset;
                                                     ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:33:27: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     int *sizes_ptr = sizes->storage->data + sizes->storageOffset;
                           ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:33:50: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     int *sizes_ptr = sizes->storage->data + sizes->storageOffset;
                                                  ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:34:29: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     int *labels_ptr = labels->storage->data + labels->storageOffset;
                             ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:34:53: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     int *labels_ptr = labels->storage->data + labels->storageOffset;
                                                     ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:35:39: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     int *label_sizes_ptr = label_sizes->storage->data + label_sizes->storageOffset;
                                       ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:35:68: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     int *label_sizes_ptr = label_sizes->storage->data + label_sizes->storageOffset;
                                                                    ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:36:29: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     float *costs_ptr = costs->storage->data + costs->storageOffset;
                             ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:36:52: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
     float *costs_ptr = costs->storage->data + costs->storageOffset;
                                                    ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:50:35: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
                        (int) probs->size[2], minibatch_size,
                                   ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:57:38: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
                      sizes_ptr, probs->size[2],
                                      ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp: In function ‘int gpu_ctc(THCTensor*, THCTensor*, THTensor*, THTensor*, THTensor*, int, THTensor*)’:
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:73:32: error: invalid use of incomplete type ‘THCTensor {aka struct THCTensor}’
        float *probs_ptr = probs->storage->data + probs->storageOffset;
                                ^
In file included from generic/THCTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCGenerateAllTypes.h:17,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:18,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/generic/THCTensor.h:7:16: error: forward declaration of ‘THCTensor {aka struct THCTensor}’
 typedef struct THCTensor THCTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:73:55: error: invalid use of incomplete type ‘THCTensor {aka struct THCTensor}’
        float *probs_ptr = probs->storage->data + probs->storageOffset;
                                                       ^
In file included from generic/THCTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCGenerateAllTypes.h:17,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:18,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/generic/THCTensor.h:7:16: error: forward declaration of ‘THCTensor {aka struct THCTensor}’
 typedef struct THCTensor THCTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:75:17: error: invalid use of incomplete type ‘THCTensor {aka struct THCTensor}’
        if (grads->storage) {
                 ^
In file included from generic/THCTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCGenerateAllTypes.h:17,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:18,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/generic/THCTensor.h:7:16: error: forward declaration of ‘THCTensor {aka struct THCTensor}’
 typedef struct THCTensor THCTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:76:33: error: invalid use of incomplete type ‘THCTensor {aka struct THCTensor}’
                grads_ptr = grads->storage->data + grads->storageOffset;
                                 ^
In file included from generic/THCTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCGenerateAllTypes.h:17,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:18,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/generic/THCTensor.h:7:16: error: forward declaration of ‘THCTensor {aka struct THCTensor}’
 typedef struct THCTensor THCTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:76:56: error: invalid use of incomplete type ‘THCTensor {aka struct THCTensor}’
                grads_ptr = grads->storage->data + grads->storageOffset;
                                                        ^
In file included from generic/THCTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCGenerateAllTypes.h:17,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:18,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/generic/THCTensor.h:7:16: error: forward declaration of ‘THCTensor {aka struct THCTensor}’
 typedef struct THCTensor THCTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:81:30: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        int *sizes_ptr = sizes->storage->data + sizes->storageOffset;
                              ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:81:53: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        int *sizes_ptr = sizes->storage->data + sizes->storageOffset;
                                                     ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:82:32: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        int *labels_ptr = labels->storage->data + labels->storageOffset;
                                ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:82:56: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        int *labels_ptr = labels->storage->data + labels->storageOffset;
                                                        ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:83:42: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        int *label_sizes_ptr = label_sizes->storage->data + label_sizes->storageOffset;
                                          ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:83:71: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        int *label_sizes_ptr = label_sizes->storage->data + label_sizes->storageOffset;
                                                                       ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:84:32: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        float *costs_ptr = costs->storage->data + costs->storageOffset;
                                ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:84:55: error: invalid use of incomplete type ‘THTensor {aka struct THTensor}’
        float *costs_ptr = costs->storage->data + costs->storageOffset;
                                                       ^
In file included from generic/THTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateFloatTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THGenerateAllTypes.h:10,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/THTensor.h:11,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:4,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/TH/generic/THTensor.h:10:16: error: forward declaration of ‘THTensor {aka struct THTensor}’
 typedef struct THTensor THTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:93:38: error: invalid use of incomplete type ‘THCTensor {aka struct THCTensor}’
                           (int) probs->size[2], minibatch_size,
                                      ^
In file included from generic/THCTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCGenerateAllTypes.h:17,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:18,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/generic/THCTensor.h:7:16: error: forward declaration of ‘THCTensor {aka struct THCTensor}’
 typedef struct THCTensor THCTensor;
                ^
/home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:101:41: error: invalid use of incomplete type ‘THCTensor {aka struct THCTensor}’
                         sizes_ptr, probs->size[2],
                                         ^
In file included from generic/THCTensor.h:1:0,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCGenerateAllTypes.h:17,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THCTensor.h:18,
                 from /home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/THC.h:13,
                 from /home/jbaik/setup/pytorch/sn.warp-ctc/pytorch_binding/src/binding.cpp:9:
/home/jbaik/.pyenv/versions/3.6.5/lib/python3.6/site-packages/torch/utils/ffi/../../lib/include/THC/generic/THCTensor.h:7:16: error: forward declaration of ‘THCTensor {aka struct THCTensor}’
 typedef struct THCTensor THCTensor;
                ^
error: command 'gcc' failed with exit status 1

import torch
from warpctc_pytorch import CTCLoss
import numpy as np
from torch.autograd import Variable

i = 1
criterion = CTCLoss()
criterion = criterion.cuda()
a = np.load('preds_%d.npy' % i)
b = np.load('text_%d.npy' % i)
c = np.load('preds_size_%d.npy' % i)
d = np.load('length_%d.npy' % i)

#a = Variable(torch.from_numpy(a)).cuda()
#b = Variable(torch.from_numpy(b)).cuda()
#c = Variable(torch.from_numpy(c)).cuda()
#d = Variable(torch.from_numpy(d)).cuda()

a = torch.from_numpy(a).cuda()
b = torch.from_numpy(b).cuda()
c = torch.from_numpy(c).cuda()
d = torch.from_numpy(d).cuda()

print(a.dtype)
print(b.dtype)
print(c.dtype)
print(d.dtype)

cost = criterion(a, b, c, d) / 64
print('cost:', cost)

Epochs:[1]/[25]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 215/215 [00:07<00:00, 29.54it/s]
train loss (min, avg, max): (-0.276, nan, 1152.610)
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 91/91 [00:01<00:00, 67.98it/s]
validation loss (min, avg, max): (inf, nan, -inf)
Epochs:[2]/[25]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 215/215 [00:06<00:00, 31.24it/s]
train loss (min, avg, max): (inf, nan, -inf)
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 91/91 [00:01<00:00, 69.84it/s]
validation loss (min, avg, max): (0.000, nan, 0.000)
Epochs:[3]/[25]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 215/215 [00:06<00:00, 33.08it/s]
train loss (min, avg, max): (1.000, nan, 1.000)
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 91/91 [00:01<00:00, 70.82it/s]
validation loss (min, avg, max): (inf, nan, -inf)

clang -Wno-unused-result -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -fwrapv -O3 -Wall -I/usr/local/lib/python3.7/site-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python3.7/site-packages/torch/utils/ffi/../../lib/include/TH -I/Users/Chandrachud/StillMind/warp-ctc/include -I/usr/local/include -I/usr/local/opt/openssl/include -I/usr/local/opt/sqlite/include -I/usr/local/Cellar/python/3.7.0/Frameworks/Python.framework/Versions/3.7/include/python3.7m -c /Users/Chandrachud/StillMind/warp-ctc/pytorch_binding/src/binding.cpp -o build/temp.macosx-10.13-x86_64-3.7/Users/Chandrachud/StillMind/warp-ctc/pytorch_binding/src/binding.o -std=c99 -std=c++11 -fPIC -std=c99
error: invalid argument '-std=c99' not allowed with 'C++'
error: command 'clang' failed with exit status 1