invalidargument

[akshadaas]

i got the following error.
InvalidArgumentError Traceback (most recent call last)
~/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1658 try:
-> 1659 c_op = c_api.TF_FinishOperation(op_desc)
1660 except errors.InvalidArgumentError as e:

InvalidArgumentError: Dimensions must be equal, but are 16 and 752 for 'decoder_1/dense_4/MatMul' (op: 'MatMul') with input shapes: [?,16], [752,512].

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last)
in
57 class_mode='categorical', shuffle=True)
58
---> 59 train_model, eval_model, manipulate_model = CapsNet(input_shape=(28, 28, 3), n_class=47, routings=3)
60 # compile the model
61

in CapsNet(input_shape, n_class, routings)
27 decoder.add(layers.Dense(np.prod(input_shape), activation='sigmoid'))
28 decoder.add(layers.Reshape(target_shape=input_shape, name='out_recon'))
---> 29 print(decoder(masked_by_y))
30
31 # Models for training and evaluation (prediction)

~/anaconda3/lib/python3.7/site-packages/keras/engine/topology.py in call(self, inputs, **kwargs)
601
602 # Actually call the layer, collecting output(s), mask(s), and shape(s).
--> 603 output = self.call(inputs, **kwargs)
604 output_mask = self.compute_mask(inputs, previous_mask)
605

~/anaconda3/lib/python3.7/site-packages/keras/models.py in call(self, inputs, mask)
544 if not self.built:
545 self.build()
--> 546 return self.model.call(inputs, mask)
547
548 def build(self, input_shape=None):

~/anaconda3/lib/python3.7/site-packages/keras/engine/topology.py in call(self, inputs, mask)
2059 return self._output_tensor_cache[cache_key]
2060 else:
-> 2061 output_tensors, _, _ = self.run_internal_graph(inputs, masks)
2062 return output_tensors
2063

~/anaconda3/lib/python3.7/site-packages/keras/engine/topology.py in run_internal_graph(self, inputs, masks)
2210 if 'mask' not in kwargs:
2211 kwargs['mask'] = computed_mask
-> 2212 output_tensors = _to_list(layer.call(computed_tensor, **kwargs))
2213 output_masks = _to_list(layer.compute_mask(computed_tensor,
2214 computed_mask))

~/anaconda3/lib/python3.7/site-packages/keras/layers/core.py in call(self, inputs)
841
842 def call(self, inputs):
--> 843 output = K.dot(inputs, self.kernel)
844 if self.use_bias:
845 output = K.bias_add(output, self.bias)

~/anaconda3/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py in dot(x, y)
1050 out = tf.sparse_tensor_dense_matmul(x, y)
1051 else:
-> 1052 out = tf.matmul(x, y)
1053 return out
1054

~/anaconda3/lib/python3.7/site-packages/tensorflow/python/ops/math_ops.py in matmul(a, b, transpose_a, transpose_b, adjoint_a, adjoint_b, a_is_sparse, b_is_sparse, name)
2453 else:
2454 return gen_math_ops.mat_mul(
-> 2455 a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
2456
2457

~/anaconda3/lib/python3.7/site-packages/tensorflow/python/ops/gen_math_ops.py in mat_mul(a, b, transpose_a, transpose_b, name)
5331 _, _, _op = _op_def_lib._apply_op_helper(
5332 "MatMul", a=a, b=b, transpose_a=transpose_a, transpose_b=transpose_b,
-> 5333 name=name)
5334 _result = _op.outputs[:]
5335 _inputs_flat = _op.inputs

~/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
786 op = g.create_op(op_type_name, inputs, output_types, name=scope,
787 input_types=input_types, attrs=attr_protos,
--> 788 op_def=op_def)
789 return output_structure, op_def.is_stateful, op
790

~/anaconda3/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
505 'in a future version' if date is None else ('after %s' % date),
506 instructions)
--> 507 return func(*args, **kwargs)
508
509 doc = _add_deprecated_arg_notice_to_docstring(

~/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in create_op(failed resolving arguments)
3298 input_types=input_types,
3299 original_op=self._default_original_op,
-> 3300 op_def=op_def)
3301 self._create_op_helper(ret, compute_device=compute_device)
3302 return ret

~/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in init(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
1821 op_def, inputs, node_def.attr)
1822 self._c_op = _create_c_op(self._graph, node_def, grouped_inputs,
-> 1823 control_input_ops)
1824
1825 # Initialize self._outputs.

~/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1660 except errors.InvalidArgumentError as e:
1661 # Convert to ValueError for backwards compatibility.
-> 1662 raise ValueError(str(e))
1663
1664 return c_op

ValueError: Dimensions must be equal, but are 16 and 752 for 'decoder_1/dense_4/MatMul' (op: 'MatMul') with input shapes: [?,16], [752,512].

@XifengGuo can you please look into it?

[akshadaas]

what is the tensorflow version?

[XifengGuo]

@akshadaas Please use the versions of keras and tensorflow specified in README.md
Also, you can try this branch for Tensorflow 2.2