InvalidArgumentError Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs, op_def)
1811 try:
→ 1812 c_op = pywrap_tf_session.TF_FinishOperation(op_desc)
1813 except errors.InvalidArgumentError as e:
InvalidArgumentError: Shapes must be equal rank, but are 2 and 0
From merging shape 0 with other shapes. for ‘{{node Pack_16}} = Pack[N=2, T=DT_FLOAT, axis=0](dense_1/Softmax_41, Pack_16/values_1)’ with input shapes: [?,90], .
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
in
----> 1 inference_model = music_inference_model(LSTM_cell, densor, Ty = 50)
in music_inference_model(LSTM_cell, densor, Ty)
49 # Set “x” to be the one-hot representation of the selected value
50 # See instructions above.
—> 51 x = tf.math.argmax(out,axis=-1) #index of the note with max probability
52 x = tf.one_hot(x,n_values)
53 x = RepeatVector(1)(x)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
199 “”“Call target, and fall back on dispatchers if there is a TypeError.”""
200 try:
→ 201 return target(*args, **kwargs)
202 except (TypeError, ValueError):
203 # Note: convert_to_eager_tensor currently raises a ValueError, not a
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/math_ops.py in argmax_v2(input, axis, output_type, name)
293 if axis is None:
294 axis = 0
→ 295 return gen_math_ops.arg_max(input, axis, name=name, output_type=output_type)
296
297
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/gen_math_ops.py in arg_max(input, dimension, output_type, name)
856 try:
857 return arg_max_eager_fallback(
→ 858 input, dimension, output_type=output_type, name=name, ctx=_ctx)
859 except _core._SymbolicException:
860 pass # Add nodes to the TensorFlow graph.
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/gen_math_ops.py in arg_max_eager_fallback(input, dimension, output_type, name, ctx)
884 output_type = _dtypes.int64
885 output_type = _execute.make_type(output_type, “output_type”)
→ 886 _attr_T, (input,) = _execute.args_to_matching_eager([input], ctx)
887 _attr_Tidx, (dimension,) = _execute.args_to_matching_eager([dimension], ctx, _dtypes.int32)
888 _inputs_flat = [input, dimension]
/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/execute.py in args_to_matching_eager(l, ctx, default_dtype)
261 ret.append(
262 ops.convert_to_tensor(
→ 263 t, dtype, preferred_dtype=default_dtype, ctx=ctx))
264 if dtype is None:
265 dtype = ret[-1].dtype
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types)
1497
1498 if ret is None:
→ 1499 ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
1500
1501 if ret is NotImplemented:
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py in _autopacking_conversion_function(v, dtype, name, as_ref)
1500 elif dtype != inferred_dtype:
1501 v = nest.map_structure(_cast_nested_seqs_to_dtype(dtype), v)
→ 1502 return _autopacking_helper(v, dtype, name or “packed”)
1503
1504
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py in _autopacking_helper(list_or_tuple, dtype, name)
1436 elems_as_tensors.append(
1437 constant_op.constant(elem, dtype=dtype, name=str(i)))
→ 1438 return gen_array_ops.pack(elems_as_tensors, name=scope)
1439 else:
1440 return converted_elems
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/gen_array_ops.py in pack(values, axis, name)
6475 axis = _execute.make_int(axis, “axis”)
6476 _, _, _op, _outputs = _op_def_library._apply_op_helper(
→ 6477 “Pack”, values=values, axis=axis, name=name)
6478 _result = _outputs[:]
6479 if _execute.must_record_gradient():
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(op_type_name, name, **keywords)
742 op = g._create_op_internal(op_type_name, inputs, dtypes=None,
743 name=scope, input_types=input_types,
→ 744 attrs=attr_protos, op_def=op_def)
745
746 # outputs is returned as a separate return value so that the output
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py in _create_op_internal(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device)
591 return super(FuncGraph, self)._create_op_internal( # pylint: disable=protected-access
592 op_type, inputs, dtypes, input_types, name, attrs, op_def,
→ 593 compute_device)
594
595 def capture(self, tensor, name=None, shape=None):
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_op_internal(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device)
3483 input_types=input_types,
3484 original_op=self._default_original_op,
→ 3485 op_def=op_def)
3486 self._create_op_helper(ret, compute_device=compute_device)
3487 return ret
/opt/conda/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)
1973 op_def = self._graph._get_op_def(node_def.op)
1974 self._c_op = _create_c_op(self._graph, node_def, inputs,
→ 1975 control_input_ops, op_def)
1976 name = compat.as_str(node_def.name)
1977 # pylint: enable=protected-access
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs, op_def)
1813 except errors.InvalidArgumentError as e:
1814 # Convert to ValueError for backwards compatibility.
→ 1815 raise ValueError(str(e))
1816
1817 return c_op
ValueError: Shapes must be equal rank, but are 2 and 0
From merging shape 0 with other shapes. for ‘{{node Pack_16}} = Pack[N=2, T=DT_FLOAT, axis=0](dense_1/Softmax_41, Pack_16/values_1)’ with input shapes: [?,90], .