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トップに関する質問mnist オートエンコーダについて

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Tracebackを追加しました

2021/07/24 17:41

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tkrd
tkrd

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test CHANGED
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test CHANGED
@@ -2,6 +2,190 @@
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+ ```Traceback
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+ in <module>()
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+
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+ 27 decoder_layer = autoencoder.layers[-1]
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+ 28 # encodeされた画像データを再構成する部分
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+ ---> 29 decoder = Model(encoded_input, decoder_layer(encoded_input))
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+ 30
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+ 31 # AdaDeltaで最適化, loss関数はbinary_crossentropy
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+
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
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+
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+ 968 if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
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+ 969 return self._functional_construction_call(inputs, args, kwargs,
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+ --> 970 input_list)
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+ 971
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+ 972 # Maintains info about the `Layer.call` stack.
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
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+ 1106 # Check input assumptions set after layer building, e.g. input shape.
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+ 1107 outputs = self._keras_tensor_symbolic_call(
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+ -> 1108 inputs, input_masks, args, kwargs)
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+ 1109
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+ 1110 if outputs is None:
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/base_layer.py in _keras_tensor_symbolic_call(self, inputs, input_masks, args, kwargs)
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+ 838 return nest.map_structure(keras_tensor.KerasTensor, output_signature)
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+ 839 else:
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+ --> 840 return self._infer_output_signature(inputs, args, kwargs, input_masks)
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+ 841
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+ 842 def _infer_output_signature(self, inputs, args, kwargs, input_masks):
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/base_layer.py in _infer_output_signature(self, inputs, args, kwargs, input_masks)
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+ 878 self._maybe_build(inputs)
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+ 879 inputs = self._maybe_cast_inputs(inputs)
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+ --> 880 outputs = call_fn(inputs, *args, **kwargs)
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+ 881
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+ 882 self._handle_activity_regularization(inputs, outputs)
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/layers/core.py in call(self, inputs)
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+ 1240 self.kernel, ids, weights, combiner='sum')
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+ 1241 else:
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+ -> 1242 outputs = gen_math_ops.MatMul(a=inputs, b=self.kernel)
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+ 1243 # Broadcast kernel to inputs.
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+ 1244 else:
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/tf_export.py in wrapper(*args, **kwargs)
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+ 402 'Please pass these args as kwargs instead.'
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+ 403 .format(f=f.__name__, kwargs=f_argspec.args))
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+ --> 404 return f(**kwargs)
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+ 405
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+ 406 return tf_decorator.make_decorator(f, wrapper, decorator_argspec=f_argspec)
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/gen_math_ops.py in mat_mul(a, b, transpose_a, transpose_b, name)
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+ 5716 _, _, _op, _outputs = _op_def_library._apply_op_helper(
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+ 5717 "MatMul", a=a, b=b, transpose_a=transpose_a, transpose_b=transpose_b,
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+ -> 5718 name=name)
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+ 5719 _result = _outputs[:]
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+ 5720 if _execute.must_record_gradient():
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(op_type_name, name, **keywords)
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+ 748 op = g._create_op_internal(op_type_name, inputs, dtypes=None,
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+ 749 name=scope, input_types=input_types,
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+ --> 750 attrs=attr_protos, op_def=op_def)
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+ 751
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+ 752 # `outputs` is returned as a separate return value so that the output
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in _create_op_internal(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device)
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+ 599 return super(FuncGraph, self)._create_op_internal( # pylint: disable=protected-access
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+ 600 op_type, captured_inputs, dtypes, input_types, name, attrs, op_def,
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+ --> 601 compute_device)
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+ 602
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+ 603 def capture(self, tensor, name=None, shape=None):
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/ops.py in _create_op_internal(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device)
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+ 3563 input_types=input_types,
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+ 3564 original_op=self._default_original_op,
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+ -> 3565 op_def=op_def)
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+ 3566 self._create_op_helper(ret, compute_device=compute_device)
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+ 3567 return ret
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
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+ 2040 op_def = self._graph._get_op_def(node_def.op)
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+ 2041 self._c_op = _create_c_op(self._graph, node_def, inputs,
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+ -> 2042 control_input_ops, op_def)
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+ 2043 name = compat.as_str(node_def.name)
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+ 2044
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+ /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs, op_def)
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+ 1881 except errors.InvalidArgumentError as e:
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+ 1882 # Convert to ValueError for backwards compatibility.
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+ -> 1883 raise ValueError(str(e))
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+ 1884
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+ 1885 return c_op
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+ ```
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  ```Error
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  ValueError: Dimensions must be equal, but are 32 and 128 for '{{node dense_5/MatMul}} = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false](Placeholder, dense_5/MatMul/ReadVariableOp)' with input shapes: [?,32], [128,784].