---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\common_shapes.py in _call_cpp_shape_fn_impl(op, input_tensors_needed, input_tensors_as_shapes_needed, debug_python_shape_fn, require_shape_fn)
669 node_def_str, input_shapes, input_tensors, input_tensors_as_shapes,
--> 670 status)
671 except errors.InvalidArgumentError as err:
C:\Anaconda3\lib\contextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()
468 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 469 pywrap_tensorflow.TF_GetCode(status))
470 finally:
InvalidArgumentError: Negative dimension size caused by subtracting 3 from 1 for 'Conv2D_4' (op: 'Conv2D') with input shapes: [?,480,1,640], [3,3,640,16].
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-17-9447719af6a8> in <module>()
1 input_img = Input(shape=(x, y, 1)) # adapt this if using `channels_first` image data format
2
----> 3 x = Conv2D(16, 3, 3, activation='relu')(input_img)
4 x = MaxPooling2D((2, 2), padding='same')(x)
5 x = Conv2D(8, 3, 3, activation='relu')(x)
C:\Anaconda3\lib\site-packages\keras\engine\topology.py in __call__(self, x, mask)
483 if inbound_layers:
484 # this will call layer.build() if necessary
--> 485 self.add_inbound_node(inbound_layers, node_indices, tensor_indices)
486 input_added = True
487
C:\Anaconda3\lib\site-packages\keras\engine\topology.py in add_inbound_node(self, inbound_layers, node_indices, tensor_indices)
541 # creating the node automatically updates self.inbound_nodes
542 # as well as outbound_nodes on inbound layers.
--> 543 Node.create_node(self, inbound_layers, node_indices, tensor_indices)
544
545 def get_output_shape_for(self, input_shape):
C:\Anaconda3\lib\site-packages\keras\engine\topology.py in create_node(cls, outbound_layer, inbound_layers, node_indices, tensor_indices)
146
147 if len(input_tensors) == 1:
--> 148 output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0]))
149 output_masks = to_list(outbound_layer.compute_mask(input_tensors[0], input_masks[0]))
150 # TODO: try to auto-infer shape if exception is raised by get_output_shape_for
C:\Anaconda3\lib\site-packages\keras\layers\convolutional.py in call(self, x, mask)
339 border_mode=self.border_mode,
340 dim_ordering=self.dim_ordering,
--> 341 filter_shape=self.W_shape)
342 if self.dim_ordering == 'th':
343 output = conv_out + K.reshape(self.b, (1, self.nb_filter, 1, 1))
C:\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in conv2d(x, kernel, strides, border_mode, dim_ordering, image_shape, filter_shape)
934 x = tf.transpose(x, (0, 2, 3, 1))
935 kernel = tf.transpose(kernel, (2, 3, 1, 0))
--> 936 x = tf.nn.conv2d(x, kernel, strides, padding=padding)
937 x = tf.transpose(x, (0, 3, 1, 2))
938 elif dim_ordering == 'tf':
C:\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py in conv2d(input, filter, strides, padding, use_cudnn_on_gpu, data_format, name)
394 strides=strides, padding=padding,
395 use_cudnn_on_gpu=use_cudnn_on_gpu,
--> 396 data_format=data_format, name=name)
397 return result
398
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py in apply_op(self, op_type_name, name, **keywords)
761 op = g.create_op(op_type_name, inputs, output_types, name=scope,
762 input_types=input_types, attrs=attr_protos,
--> 763 op_def=op_def)
764 if output_structure:
765 outputs = op.outputs
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in create_op(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_shapes, compute_device)
2395 original_op=self._default_original_op, op_def=op_def)
2396 if compute_shapes:
-> 2397 set_shapes_for_outputs(ret)
2398 self._add_op(ret)
2399 self._record_op_seen_by_control_dependencies(ret)
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in set_shapes_for_outputs(op)
1755 shape_func = _call_cpp_shape_fn_and_require_op
1756
-> 1757 shapes = shape_func(op)
1758 if shapes is None:
1759 raise RuntimeError(
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in call_with_requiring(op)
1705
1706 def call_with_requiring(op):
-> 1707 return call_cpp_shape_fn(op, require_shape_fn=True)
1708
1709 _call_cpp_shape_fn_and_require_op = call_with_requiring
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\common_shapes.py in call_cpp_shape_fn(op, input_tensors_needed, input_tensors_as_shapes_needed, debug_python_shape_fn, require_shape_fn)
608 res = _call_cpp_shape_fn_impl(op, input_tensors_needed,
609 input_tensors_as_shapes_needed,
--> 610 debug_python_shape_fn, require_shape_fn)
611 if not isinstance(res, dict):
612 # Handles the case where _call_cpp_shape_fn_impl calls unknown_shape(op).
C:\Anaconda3\lib\site-packages\tensorflow\python\framework\common_shapes.py in _call_cpp_shape_fn_impl(op, input_tensors_needed, input_tensors_as_shapes_needed, debug_python_shape_fn, require_shape_fn)
673 missing_shape_fn = True
674 else:
--> 675 raise ValueError(err.message)
676
677 if missing_shape_fn:
ValueError: Negative dimension size caused by subtracting 3 from 1 for 'Conv2D_4' (op: 'Conv2D') with input shapes: [?,480,1,640], [3,3,640,16].