Week 3 Programming Assignment

Please help me with the error

one_hot_matrix runs successfully. but after that it says new_y_test not defined.

@Swetalin try re-running all cells above one_hot_matrix() function to make sure that all variables are initialized. I’m guessing here, but maybe the error says y_test (not new_y_test) is not defined.

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nope…it’s new_y_test…and i already have tried re-running the cells countless times.

and in train model segment…it says ‘new_y_train’ not defined

It’s done now. While reshaping I was hard coding shape of matrix in one_hot_matrix section. I have corrected that and it runs now. :slight_smile:

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Good job @Swetalin !

What I noticed in your screenshots was that error 'new_y_test' is not defined was returned by cell [20]. Meanwhile the cell above that also had some error - that’s the one the one that initializes new_y_test and new_y_train by mapping them with one_hot_matrix, and has a large, scrollable error block. Since new_y_test initialization statement ran into an error, the next cell [20] throws error when you try to access it. Same goes for new_y_train.

yeah…got it…thank you @vjmalkoti :slight_smile:

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Hi, I’m getting the same error. Could you please explain how you resolved it. Thank you!

Hey @Swetalin ,
Could you please tell me how you programed the tf.cast method in the sigmoid function block of code?
thank you.

Hello there,

Can someone be kind enough and please explain how this error was resolved? Unlike @Swetalin I am not hardcoding anything and the assertions work in the first cell, but then I get the error:

NameError                                 Traceback (most recent call last)
<ipython-input-61-5bb8dee1e239> in <module>
----> 1 print(next(iter(new_y_test)))

NameError: name 'new_y_test' is not defined

The process:

  • One_hot is equal to the reshaped tf.one_hot.

The formula is quite simple really, so I am not sure what the grader’s problem is.

Any pointers? (thanks!)

Hi, @Jonathanlugo.

Did you run the cell right above where new_y_test and new_y_train are initialized? Did it throw any errors?

Hi @nramon !, yup, it seemed to have worked:

Test 1: tf.Tensor([0. 1. 0. 0.], shape=(4,), dtype=float32)
Test 2: tf.Tensor([0. 0. 1. 0.], shape=(4,), dtype=float32)
All test passed

There should be another cell after that one that reads:

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

Try creating it if it’s not there :thinking:

Hi @nramon , yup, you are right, the cell exists but when I run it it produces the following output:

ValueError                                Traceback (most recent call last)
<ipython-input-118-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)
   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)
--> 986       func_outputs = python_func(*func_args, **func_kwargs)
    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,)
-> 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-106-d5b47b10f009>:17 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
    /opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:3485 _create_op_internal
    /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 am not sure what I should change in here… Thank you for your help!

I’ve seen that error before. Take a look at this post :slight_smile:

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Hi @nramon , thank you, that solved the problem, albeit I have to say that it was tricky ( I am not familiar with TensorFlow’s syntax and this information was not in the exercise description - or maybe I just missed it…).

I also looked into the TF’s docs and did not find that syntax.

In any case, glad that you are there somewhere there in the cloud helping us!

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Happy to help, @Jonathanlugo.

You’re right :sweat: If you’re referring to the (scalar,) syntax, it’s just a one-element tuple. A list would’ve worked too: shape=[scalar]. But it does have to be a tensor-like object.

Keep up the great work and good luck with course 3 :slight_smile: