Please help me with the error
one_hot_matrix runs successfully. but after that it says new_y_test not defined.
Please help me with the error
@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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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. 
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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
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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 
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)
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-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
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 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 
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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 
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
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