Week 3 Exercise 3 - one_hot_matrix

[ekrx]

I’m getting errors in a non-graded function. All my code is passing. However, I dont think this part uses any of the written code.

I have restarted the kernel already and still not working.

What can be wrong here?

new_y_test = y_test.map(one_hot_matrix)
new_y_train = y_train.map(one_hot_matrix)

Throws the following error:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-22-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-18-ff2a18af5d02>:16 one_hot_matrix  *
        one_hot = tf.reshape(tf.one_hot(label, depth), 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], [].

[rmwkwok]

Hello @ekrx,

Debugging your work is part of the assignment, so I am going to share with you how we can make use of the error message to help debug. Let’s look at the following part of the message:

We usually start off at the last line and the word Shape (No. 1) gave us the keyword to remember. Then looking backward, we locate the line of code which had the problem in No. 2, and if you read the line right above that, you see that it came from the function one_hot_matrix which is an assignment exercise you had implemented.

Knowing that it came from your work, it is something you can deal with.

However, there were 2 functions in that line that could complain - tf.reshape and tf.one_hot, but very quickly No. 3 told us that it was tf.reshape. Lastly, No. 4 informed us the very two inputs tf.reshape received had the shapes of [6] and [] respectively. Among the two, which one had the problem? The answer lied in No. 5 - the one of rank 0 is the problem.

I will stop here and let you do the rest of the investigation, which should be 2 steps away from the solutions. You need to figure out which one is a rank 0 input, and then figure out how to fix that input. For the first one, you can guess and confirm with your experiment, or you can google. For the second one, you can read the assignment again - the answer is there.

Cheers,
Raymond

[ekrx]

Thank you @rmwkwok
Very useful.