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View Code? Open in Web Editor NEWDeep Neural Networks for Kinship prediction using face photos
License: MIT License
Deep Neural Networks for Kinship prediction using face photos
License: MIT License
Created google colab version that is updated and better running.
https://colab.research.google.com/drive/10JmQjBVthEm2ZJN8PGVhDIU0PaTNgb61?usp=sharing
model.fit_generator(gen(train, train_person_to_images_map, batch_size=16), use_multiprocessing=True,
validation_data=gen(val, val_person_to_images_map, batch_size=16), epochs=100, verbose=2,
workers=4, callbacks=callbacks_list, steps_per_epoch=200, validation_steps=100)
This is the portion where error is showing
The error is:
ValueError: logits
and labels
must have the same shape, received ((None, 1) vs ()).
which version of tensorflow are you using?
unfortunately I've ran in too many error and warnings using v2.1
model.fit_generator(gen(train, train_person_to_images_map, batch_size=16), use_multiprocessing=True,
validation_data=gen(val, val_person_to_images_map, batch_size=16), epochs=100, verbose=2,
workers=4, callbacks=callbacks_list, steps_per_epoch=200, validation_steps=100)
Please help me with this.
cannot download the model from this website.Because s3.amazon.com is blocked by the "Great Wall" :-(
Can anyone put it on gitgub?
Please help me to resolve this.
`Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
Epoch 1/100
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
[<ipython-input-26-0f1203a024ef>](https://localhost:8080/#) in <module>()
127 model.fit_generator(gen(train, train_person_to_images_map, batch_size=16), use_multiprocessing=True,
128 validation_data=gen(val, val_person_to_images_map, batch_size=16), epochs=100, verbose=2,
--> 129 workers=4, callbacks=callbacks_list, steps_per_epoch=200, validation_steps=100)
130
131 test_path = "../input/test/"
2 frames
[/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py](https://localhost:8080/#) in autograph_handler(*args, **kwargs)
1145 except Exception as e: # pylint:disable=broad-except
1146 if hasattr(e, "ag_error_metadata"):
-> 1147 raise e.ag_error_metadata.to_exception(e)
1148 else:
1149 raise
ValueError: in user code:
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function *
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step **
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 860, in train_step
loss = self.compute_loss(x, y, y_pred, sample_weight)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 919, in compute_loss
y, y_pred, sample_weight, regularization_losses=self.losses)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 201, in __call__
loss_value = loss_obj(y_t, y_p, sample_weight=sw)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 141, in __call__
losses = call_fn(y_true, y_pred)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 245, in call **
return ag_fn(y_true, y_pred, **self._fn_kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 1932, in binary_crossentropy
backend.binary_crossentropy(y_true, y_pred, from_logits=from_logits),
File "/usr/local/lib/python3.7/dist-packages/keras/backend.py", line 5247, in binary_crossentropy
return tf.nn.sigmoid_cross_entropy_with_logits(labels=target, logits=output)
ValueError: `logits` and `labels` must have the same shape, received ((None, 1) vs ()).`
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