Problem at C5W3A1 Exercise 2 - modelf
Please post the entire error trace.
This is the Neural Machine Translation assignment. Both of those shapes appear in the logic of the model, so it might be necessary to see the initial part of the exception trace to understand where in the logic the error is happening. I added some print statements to my code and here’s what I see when I run that test cell:
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
before repeator s_prev.shape = (None, 64)
after repeator s_prev.shape = (None, 30, 64)
[['InputLayer', [(None, 30, 37)], 0], ['InputLayer', [(None, 64)], 0], ['Bidirectional', (None, 30, 64), 17920], ['RepeatVector', (None, 30, 64), 0, 30], ['Concatenate', (None, 30, 128), 0], ['Dense', (None, 30, 10), 1290, 'tanh'], ['Dense', (None, 30, 1), 11, 'relu'], ['Activation', (None, 30, 1), 0], ['Dot', (None, 1, 64), 0], ['InputLayer', [(None, 64)], 0], ['LSTM', [(None, 64), (None, 64), (None, 64)], 33024, [(None, 1, 64), (None, 64), (None, 64)], 'tanh'], ['Dense', (None, 11), 715, 'softmax']]
All tests passed!
I added another cell to print the model in a more readable form:
print("Generated model:")
for index, a in enumerate(summary(model)):
print(f"layer {index}: {a}")
print("Expected model:")
for index, a in enumerate(expected_summary):
print(f"layer {index}: {a}")
Here’s what I get:
Generated model:
layer 0: ['InputLayer', [(None, 30, 37)], 0]
layer 1: ['InputLayer', [(None, 64)], 0]
layer 2: ['Bidirectional', (None, 30, 64), 17920]
layer 3: ['RepeatVector', (None, 30, 64), 0, 30]
layer 4: ['Concatenate', (None, 30, 128), 0]
layer 5: ['Dense', (None, 30, 10), 1290, 'tanh']
layer 6: ['Dense', (None, 30, 1), 11, 'relu']
layer 7: ['Activation', (None, 30, 1), 0]
layer 8: ['Dot', (None, 1, 64), 0]
layer 9: ['InputLayer', [(None, 64)], 0]
layer 10: ['LSTM', [(None, 64), (None, 64), (None, 64)], 33024, [(None, 1, 64), (None, 64), (None, 64)], 'tanh']
layer 11: ['Dense', (None, 11), 715, 'softmax']
Expected model:
layer 0: ['InputLayer', [(None, 30, 37)], 0]
layer 1: ['InputLayer', [(None, 64)], 0]
layer 2: ['Bidirectional', (None, 30, 64), 17920]
layer 3: ['RepeatVector', (None, 30, 64), 0, 30]
layer 4: ['Concatenate', (None, 30, 128), 0]
layer 5: ['Dense', (None, 30, 10), 1290, 'tanh']
layer 6: ['Dense', (None, 30, 1), 11, 'relu']
layer 7: ['Activation', (None, 30, 1), 0]
layer 8: ['Dot', (None, 1, 64), 0]
layer 9: ['InputLayer', [(None, 64)], 0]
layer 10: ['LSTM', [(None, 64), (None, 64), (None, 64)], 33024, [(None, 1, 64), (None, 64), (None, 64)], 'tanh']
layer 11: ['Dense', (None, 11), 715, 'softmax']
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs, op_def)
1811 try:
-> 1812 c_op = pywrap_tf_session.TF_FinishOperation(op_desc)
1813 except errors.InvalidArgumentError as e:
InvalidArgumentError: Shape must be rank 2 but is rank 3 for '{{node concatenate/concat}} = ConcatV2[N=2, T=DT_FLOAT, Tidx=DT_INT32](bidirectional/concat, repeat_vector/Tile, concatenate/concat/axis)' with input shapes: [?,64], [?,30,64], [].
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-12-1492e4d59c1c> in <module>
34
35
---> 36 modelf_test(modelf)
<ipython-input-12-1492e4d59c1c> in modelf_test(target)
11
12
---> 13 model = target(Tx, Ty, n_a, n_s, len_human_vocab)
14
15 print(summary(model))
<ipython-input-11-c76f00690ede> in modelf(Tx, Ty, n_a, n_s, human_vocab_size, machine_vocab_size)
42
43 # Step 2.A: Perform one step of the attention mechanism to get back the context vector at step t (≈ 1 line)
---> 44 context = one_step_attention(a, s)
45
46 # Step 2.B: Apply the post-attention LSTM cell to the "context" vector. (≈ 1 line)
<ipython-input-8-03dbbcad282b> 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)
2879 return ragged_concat_ops.concat(tensors, axis)
2880 else:
-> 2881 return array_ops.concat([to_dense(x) for x in tensors], axis)
2882
2883
/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/ops/array_ops.py in concat(values, axis, name)
1652 dtype=dtypes.int32).get_shape().assert_has_rank(0)
1653 return identity(values[0], name=name)
-> 1654 return gen_array_ops.concat_v2(values=values, axis=axis, name=name)
1655
1656
/opt/conda/lib/python3.7/site-packages/tensorflow/python/ops/gen_array_ops.py in concat_v2(values, axis, name)
1220 _attr_N = len(values)
1221 _, _, _op, _outputs = _op_def_library._apply_op_helper(
-> 1222 "ConcatV2", values=values, axis=axis, name=name)
1223 _result = _outputs[:]
1224 if _execute.must_record_gradient():
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(op_type_name, name, **keywords)
742 op = g._create_op_internal(op_type_name, inputs, dtypes=None,
743 name=scope, input_types=input_types,
--> 744 attrs=attr_protos, op_def=op_def)
745
746 # `outputs` is returned as a separate return value so that the output
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py in _create_op_internal(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device)
591 return super(FuncGraph, self)._create_op_internal( # pylint: disable=protected-access
592 op_type, inputs, dtypes, input_types, name, attrs, op_def,
--> 593 compute_device)
594
595 def capture(self, tensor, name=None, shape=None):
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_op_internal(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_device)
3483 input_types=input_types,
3484 original_op=self._default_original_op,
-> 3485 op_def=op_def)
3486 self._create_op_helper(ret, compute_device=compute_device)
3487 return ret
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
1973 op_def = self._graph._get_op_def(node_def.op)
1974 self._c_op = _create_c_op(self._graph, node_def, inputs,
-> 1975 control_input_ops, op_def)
1976 name = compat.as_str(node_def.name)
1977 # pylint: enable=protected-access
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs, op_def)
1813 except errors.InvalidArgumentError as e:
1814 # Convert to ValueError for backwards compatibility.
-> 1815 raise ValueError(str(e))
1816
1817 return c_op
ValueError: Shape must be rank 2 but is rank 3 for '{{node concatenate/concat}} = ConcatV2[N=2, T=DT_FLOAT, Tidx=DT_INT32](bidirectional/concat, repeat_vector/Tile, concatenate/concat/axis)' with input shapes: [?,64], [?,30,64], [].
I would guess there is an error in the value of ‘a’ in this line:
context = one_step_attention(a, s)
It is set in the prior line a = Bidirectional(LSTM(...
Oh yes yes.
I forget to set return_sequences=True.
Thank you sir.
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