I implemented the one_hot_matrix where I output the one hot encoding using this line of code:
one_hot = tf.reshape(tf.one_hot(label, depth, axis = 0), depth)
return one_hot
and all tests were passed succesfully.
However, later on in this code block:
new_y_test = y_test.map(one_hot_matrix)
new_y_train = y_train.map(one_hot_matrix)
it gives out the following error:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-123-cefe2ef5b6b2> in <module>
----> 1 new_y_test = y_test.map(one_hot_matrix)
2 new_y_train = y_train.map(one_hot_matrix)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in map(self, map_func, num_parallel_calls, deterministic)
1693 """
1694 if num_parallel_calls is None:
-> 1695 return MapDataset(self, map_func, preserve_cardinality=True)
1696 else:
1697 return ParallelMapDataset(
/opt/conda/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in __init__(self, input_dataset, map_func, use_inter_op_parallelism, preserve_cardinality, use_legacy_function)
4043 self._transformation_name(),
4044 dataset=input_dataset,
-> 4045 use_legacy_function=use_legacy_function)
4046 variant_tensor = gen_dataset_ops.map_dataset(
4047 input_dataset._variant_tensor, # pylint: disable=protected-access
/opt/conda/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in __init__(self, func, transformation_name, dataset, input_classes, input_shapes, input_types, input_structure, add_to_graph, use_legacy_function, defun_kwargs)
3369 with tracking.resource_tracker_scope(resource_tracker):
3370 # TODO(b/141462134): Switch to using garbage collection.
-> 3371 self._function = wrapper_fn.get_concrete_function()
3372 if add_to_graph:
3373 self._function.add_to_graph(ops.get_default_graph())
/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/function.py in get_concrete_function(self, *args, **kwargs)
2937 """
2938 graph_function = self._get_concrete_function_garbage_collected(
-> 2939 *args, **kwargs)
2940 graph_function._garbage_collector.release() # pylint: disable=protected-access
2941 return graph_function
/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _get_concrete_function_garbage_collected(self, *args, **kwargs)
2904 args, kwargs = None, None
2905 with self._lock:
-> 2906 graph_function, args, kwargs = self._maybe_define_function(args, kwargs)
2907 seen_names = set()
2908 captured = object_identity.ObjectIdentitySet(
/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _maybe_define_function(self, args, kwargs)
3211
3212 self._function_cache.missed.add(call_context_key)
-> 3213 graph_function = self._create_graph_function(args, kwargs)
3214 self._function_cache.primary[cache_key] = graph_function
3215 return graph_function, args, kwargs
/opt/conda/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
3073 arg_names=arg_names,
3074 override_flat_arg_shapes=override_flat_arg_shapes,
-> 3075 capture_by_value=self._capture_by_value),
3076 self._function_attributes,
3077 function_spec=self.function_spec,
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)
984 _, original_func = tf_decorator.unwrap(python_func)
985
--> 986 func_outputs = python_func(*func_args, **func_kwargs)
987
988 # invariant: `func_outputs` contains only Tensors, CompositeTensors,
/opt/conda/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in wrapper_fn(*args)
3362 attributes=defun_kwargs)
3363 def wrapper_fn(*args): # pylint: disable=missing-docstring
-> 3364 ret = _wrapper_helper(*args)
3365 ret = structure.to_tensor_list(self._output_structure, ret)
3366 return [ops.convert_to_tensor(t) for t in ret]
/opt/conda/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in _wrapper_helper(*args)
3297 nested_args = (nested_args,)
3298
-> 3299 ret = autograph.tf_convert(func, ag_ctx)(*nested_args)
3300 # If `func` returns a list of tensors, `nest.flatten()` and
3301 # `ops.convert_to_tensor()` would conspire to attempt to stack
/opt/conda/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py in wrapper(*args, **kwargs)
256 except Exception as e: # pylint:disable=broad-except
257 if hasattr(e, 'ag_error_metadata'):
--> 258 raise e.ag_error_metadata.to_exception(e)
259 else:
260 raise
ValueError: in user code:
<ipython-input-72-4d1c2aa9c8ff>:17 one_hot_matrix *
one_hot = tf.reshape(tf.one_hot(label, depth, axis = 0), depth)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py:201 wrapper **
return target(*args, **kwargs)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py:195 reshape
result = gen_array_ops.reshape(tensor, shape, name)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/gen_array_ops.py:8234 reshape
"Reshape", tensor=tensor, shape=shape, name=name)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py:744 _apply_op_helper
attrs=attr_protos, op_def=op_def)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py:593 _create_op_internal
compute_device)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:3485 _create_op_internal
op_def=op_def)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:1975 __init__
control_input_ops, op_def)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:1815 _create_c_op
raise ValueError(str(e))
ValueError: Shape must be rank 1 but is rank 0 for '{{node Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32](one_hot, Reshape/shape)' with input shapes: [6], [].
I have to change the one hot matrix line of code to have a shape of (depth, ) instead of just ‘depth’, and then it works.
My question here is why does that happen although the tests were passed and the shapes were correct?