C5 W3A1 modelf() function problem

Course Q&A Deep Learning Specialization Sequence Models
1

My modelf function:

{moderator edit - solution code removed}

When I run modelf_test(…), I got error below, What is wrong with my code? I passed all one_step_attention_test. Thanks

AttributeError Traceback (most recent call last)
in
35
36
—> 37 modelf_test(modelf)

in modelf_test(target)
12
13
—> 14 model = target(Tx, Ty, n_a, n_s, len_human_vocab, len_machine_vocab)
15
16 print(summary(model))

in modelf(Tx, Ty, n_a, n_s, human_vocab_size, machine_vocab_size)
41
42 # Step 2.A: Perform one step of the attention mechanism to get back the context vector at step t (≈ 1 line)
—> 43 context = one_step_attention(a, s)
44
45 # Step 2.B: Apply the post-attention LSTM cell to the “context” vector. (≈ 1 line)

in one_step_attention(a, s_prev)
20 # Use concatenator to concatenate a and s_prev on the last axis (≈ 1 line)
21 # For grading purposes, please list ‘a’ first and ‘s_prev’ second, in this order.
—> 22 concat = concatenator([a, s_prev])
23 # Use densor1 to propagate concat through a small fully-connected neural network to compute the “intermediate energies” variable e. (≈1 lines)
24 e = densor1(concat)

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in call(self, *args, **kwargs)
924 if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
925 return self._functional_construction_call(inputs, args, kwargs,
→ 926 input_list)
927
928 # Maintains info about the Layer.call stack.

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
1115 try:
1116 with ops.enable_auto_cast_variables(self._compute_dtype_object):
→ 1117 outputs = call_fn(cast_inputs, *args, **kwargs)
1118
1119 except errors.OperatorNotAllowedInGraphError as e:

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/merge.py in call(self, inputs)
181 return y
182 else:
→ 183 return self._merge_function(inputs)
184
185 @tf_utils.shape_type_conversion

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/merge.py in _merge_function(self, inputs)
520
521 def _merge_function(self, inputs):
→ 522 return K.concatenate(inputs, axis=self.axis)
523
524 @tf_utils.shape_type_conversion

/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/keras/backend.py in concatenate(tensors, axis)
2868 “”"
2869 if axis < 0:
→ 2870 rank = ndim(tensors[0])
2871 if rank:
2872 axis %= rank

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/backend.py in ndim(x)
1333
1334 “”"
→ 1335 dims = x.shape._dims
1336 if dims is not None:
1337 return len(dims)

AttributeError: ‘list’ object has no attribute ‘shape’

2

The arguments you are supplying when you create the Bidirectional LSTM are different than the ones I used. If I use your arguments, I get the same error you show. Note that they essentially wrote the code for you in the instructions for this section. They also say this:

  • Remember that we want the LSTM to return a full sequence instead of just the last hidden state.

Also please note that we aren’t supposed to just post our code in a public way. Please start by just showing the error trace. If we can’t figure out how to help based on the exception messages, there are private ways to share the code.

1 Like
3

Thank you Paul.

1 Like