Comments (1)
PINTO0309
commented on June 2, 2024
$ pip show tensorflow
Name: tensorflow
Version: 2.15.0.post1
onnx2tf -i resnet18-v1-7.onnxINFO: input.5.beta: val: 1.0
INFO: output.1.output: name: tf.__operators__.add/AddV2:0 shape: (1, 1000) dtype: <dtype: 'float32'>
saved_model output started ==========================================================
saved_model output complete!
Summary on the non-converted ops:
---------------------------------
* Accepted dialects: tfl, builtin, func
* Non-Converted Ops: 48, Total Ops 89, % non-converted = 53.93 %
* 48 ARITH ops
- arith.constant: 48 occurrences (f32: 43, i32: 5)
(f32: 8)
(f32: 20)
(f32: 1)
(f32: 1)
(f32: 1)
(f32: 4)
(f32: 1)
(f32: 1)
(f32: 1)
Float32 tflite output complete!
Summary on the non-converted ops:
---------------------------------
* Accepted dialects: tfl, builtin, func
* Non-Converted Ops: 48, Total Ops 132, % non-converted = 36.36 %
* 48 ARITH ops
- arith.constant: 48 occurrences (f16: 43, i32: 5)
(f32: 8)
(f32: 20)
(f32: 43)
(f32: 1)
(f32: 1)
(f32: 1)
(f32: 4)
(f32: 1)
(f32: 1)
(f32: 1)
Float16 tflite output complete!
from onnx2tf.
Related Issues (20)
- Downgrade of ~10% on multiple weights of YoloX HOT 7
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- [ssdlite320_mobilenet_v3_large] Wrong shapes during inference HOT 2
- SavedModel saved prior to TF 2.5 detected when loading Keras model. HOT 2
- Conversion of ScatterND operator results in error HOT 2
- module 'tensorflow' has no attribute 'random' for tensorflow 2.15, but 2.14.0 does HOT 2
- Conversion of YoloV5, conversion of StridedSlice from 5d to 4d HOT 7
- Failed to convert Real-ESRGAN x4-general (NCHW) HOT 1
- Error when onnx2tf: Floating point exception (core dumped) HOT 10
- Full int8 quantized model doesn't work when "flatc" is installed on the system HOT 8
- ValueError: Exception encountered when calling layer "tf.math.multiply_46" (type TFOpLambda).
- 0 trainable parameters HOT 1
- pre_explicit_broadcast should not expend scalar tensor HOT 13
- "GEMM: Dimension mismatch" during value validation phase HOT 4
- Exclude selected operations from INT8 quantized model HOT 18
- ValueError in MaxPool Layer during ONNX to TensorFlow Conversion with 3D Input HOT 5
- The tflite detection result converted from the yolo NAS model is inaccurate. HOT 5
- Converting quantized onnx with Q/DQ representation to full int8 TFLite model HOT 2
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from onnx2tf.