Invalid placeholder in tensorflow - python-3.x

Question

I am trying to write a custom loss function as follows.
def vgg16_feature_model(flayers, weights='imagenet'):
"""
Feature exctraction VGG16 model.
# Arguments
flayers: list of strings with names of layers to get the features for.
The length of `flayers` should be > 1, otherwise the output shape
is one axis less.
weights: ether "imagenet" or path to the file with weights.
# Returns
features_model: keras.models.Model instance to extract the features.
# Raises
AssertionError: in case of `flayers` is not a list.
AssertionError: in case of length of 'flayers' < 2.
"""
assert isinstance(flayers,list), "First argument 'flayers' must be a list"
assert len(flayers) > 1, "Length of 'flayers' must be > 1."
base_model = VGG16(include_top=False, weights=weights)
vgg16_outputs = [base_model.get_layer(flayers[i]).output for i in range(len(flayers))]
features_model = Model(inputs=[base_model.input], outputs=vgg16_outputs, name='vgg16_features')
features_model.trainable = False
features_model.compile(loss='mse', optimizer='adam')
return features_model
# Losses:
# -------
def total_loss(mask, vgg16_weights='imagenet'):
"""
Total loss defined in Eq 7 of Liu et al 2018 with:
y_true = I_gt,
y_pred = I_out,
y_comp = I_comp.
"""
vgg16_lnames = ['block1_pool', 'block2_pool', 'block3_pool']
vgg_model = vgg16_feature_model(vgg16_lnames, weights=vgg16_weights)
def loss(y_true, y_pred):
mask_inv = 1 - mask
y_comp = mask * y_true + mask_inv * y_pred
print("y_pred", y_pred)
print(y_comp)
input()
vgg_out = vgg_model(y_pred)
vgg_gt = vgg_model(y_true)
print("abc-----------------------------------")
vgg_comp = vgg_model(y_comp)
print("abc")
l_valid = loss_per_pixel(y_true, y_pred, mask)
l_hole = loss_per_pixel(y_true, y_pred, mask_inv)
l_perc = loss_perc(vgg_out, vgg_gt, vgg_comp)
l_style = loss_style(vgg_out, vgg_gt, vgg_comp)
l_tv = loss_tv(y_comp, mask_inv)
return l_valid + 6.*l_hole + 0.05*l_perc + 120.*l_style + 0.1*l_tv
return loss
I am getting an error as
Traceback (most recent call last):
File "inpainter_main.py", line 46, in <module>
model = pconv_model(lr=LR_STAGE1, image_size=IMAGE_SIZE, vgg16_weights=VGG16_WEIGHTS)
File "/home/bitsy-chuck/Downloads/PConv2D-2ndimp/inpainter_utils/pconv2d_model.py", line 118, in pconv_model
model.compile(Adam(lr=lr), loss=total_loss(mask_input, vgg16_weights=vgg16_weights))
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py", line 456, in _method_wrapper
result = method(self, *args, **kwargs)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_v1.py", line 446, in compile
self._compile_weights_loss_and_weighted_metrics()
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py", line 456, in _method_wrapper
result = method(self, *args, **kwargs)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_v1.py", line 1515, in _compile_weights_loss_and_weighted_metrics
self.total_loss = self._prepare_total_loss(masks)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_v1.py", line 1575, in _prepare_total_loss
per_sample_losses = loss_fn.call(y_true, y_pred)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/losses.py", line 246, in call
return self.fn(y_true, y_pred, **self._fn_kwargs)
File "/home/bitsy-chuck/Downloads/PConv2D-2ndimp/inpainter_utils/pconv2d_loss.py", line 58, in loss
vgg_comp = vgg_model(y_comp)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 737, in __call__
base_layer_utils.create_keras_history(inputs)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py", line 186, in create_keras_history
_, created_layers = _create_keras_history_helper(tensors, set(), [])
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py", line 249, in _create_keras_history_helper
layer_inputs, processed_ops, created_layers)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer_utils.py", line 246, in _create_keras_history_helper
constants[i] = backend.function([], op_input)([])
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/backend.py", line 3632, in __call__
run_metadata=self.run_metadata)
File "/home/bitsy-chuck/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1472, in __call__
run_metadata_ptr)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'pconv2d_dec_16_target' with dtype float and shape [?,?,?,?]
[[{{node pconv2d_dec_16_target}}]]
I first thought that y_comp is not correct, but
y_pred ---> Tensor("pconv2d_dec_16/BiasAdd:0", shape=(None, 512, 512, 3), dtype=float32)
y_comp ---> Tensor("loss_1/pconv2d_dec_16_loss/add:0", shape=(None, 512, 512, 3), dtype=float32)
They both appear the same to me and it should work, according to me.
error is at line vgg_comp = vgg_model(y_comp)
Can anyone also explain why am I getting an error of placeholder?
Tf version 1.3
keras 2.2.4

Answer 1

placeholder errors are usually due to tensorflow versions. I had the exact same error and it was fixed when I installed keras first and then tensorflow first. Using anaconda might help as they cache all the files when you uninstall so it is easy to install again without having to download the entire thing again.
There might be some other fix, I believe, but this fixed mine.