Hi,
i was trying to download and run te workspace of Transfer_learning_with_MobileNet_v1.
I followed the instructions according to (both splitting up/not splitting up the zipped file):
On my Windows notebook i can unzip and open the workspace, as well as run all cells until cell 17:
model2 = alpaca_model(IMG_SIZE, data_augmentation)
This cell gives me a lengthy error message:
NotImplementedError Traceback (most recent call last)
in
----> 1 model2 = alpaca_model(IMG_SIZE, data_augmentation)
in alpaca_model(image_shape, data_augmentation)
27
28 # apply data augmentation to the inputs
—> 29 x = data_augmentation(inputs)
30
31 # data preprocessing using the same weights the model was trained on
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in call(self, *args, **kwargs)
923 # >> model = tf.keras.Model(inputs, outputs)
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
C:\ProgramData\Anaconda3\lib\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:
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\sequential.py in call(self, inputs, training, mask)
384 kwargs[‘training’] = training
385
→ 386 outputs = layer(inputs, **kwargs)
387
388 if len(nest.flatten(outputs)) != 1:
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in call(self, *args, **kwargs)
923 # >> model = tf.keras.Model(inputs, outputs)
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
C:\ProgramData\Anaconda3\lib\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:
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\layers\preprocessing\image_preprocessing.py in call(self, inputs, training)
820 interpolation=self.interpolation)
821
→ 822 output = tf_utils.smart_cond(training, random_rotated_inputs,
823 lambda: inputs)
824 output.set_shape(inputs.shape)
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\utils\tf_utils.py in smart_cond(pred, true_fn, false_fn, name)
62 return control_flow_ops.cond(
63 pred, true_fn=true_fn, false_fn=false_fn, name=name)
—> 64 return smart_module.smart_cond(
65 pred, true_fn=true_fn, false_fn=false_fn, name=name)
66
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\framework\smart_cond.py in smart_cond(pred, true_fn, false_fn, name)
52 if pred_value is not None:
53 if pred_value:
—> 54 return true_fn()
55 else:
56 return false_fn()
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\layers\preprocessing\image_preprocessing.py in random_rotated_inputs()
816 return transform(
817 inputs,
→ 818 get_rotation_matrix(angles, img_hd, img_wd),
819 fill_mode=self.fill_mode,
820 interpolation=self.interpolation)
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\layers\preprocessing\image_preprocessing.py in get_rotation_matrix(angles, image_height, image_width, name)
720 math_ops.cos(angles)[:, None],
721 y_offset[:, None],
→ 722 array_ops.zeros((num_angles, 2), dtypes.float32),
723 ],
724 axis=1)
C:\ProgramData\Anaconda3\lib\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
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py in wrapped(*args, **kwargs)
2745
2746 def wrapped(*args, **kwargs):
→ 2747 tensor = fun(*args, **kwargs)
2748 tensor._is_zeros_tensor = True
2749 return tensor
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py in zeros(shape, dtype, name)
2792 # Create a constant if it won’t be very big. Otherwise create a fill
2793 # op to prevent serialized GraphDefs from becoming too large.
→ 2794 output = _constant_if_small(zero, shape, dtype, name)
2795 if output is not None:
2796 return output
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py in _constant_if_small(value, shape, dtype, name)
2730 def _constant_if_small(value, shape, dtype, name):
2731 try:
→ 2732 if np.prod(shape) < 1000:
2733 return constant(value, shape=shape, dtype=dtype, name=name)
2734 except TypeError:
<array_function internals> in prod(*args, **kwargs)
C:\ProgramData\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in prod(a, axis, dtype, out, keepdims, initial, where)
3028 10
3029 “”"
→ 3030 return _wrapreduction(a, np.multiply, ‘prod’, axis, dtype, out,
3031 keepdims=keepdims, initial=initial, where=where)
3032
C:\ProgramData\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs)
85 return reduction(axis=axis, out=out, **passkwargs)
86
—> 87 return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
88
89
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in array(self)
843
844 def array(self):
→ 845 raise NotImplementedError(
846 “Cannot convert a symbolic Tensor ({}) to a numpy array.”
847 " This error may indicate that you’re trying to pass a Tensor to"
NotImplementedError: Cannot convert a symbolic Tensor (sequential_1/random_rotation_1/rotation_matrix_1/strided_slice:0) to a numpy array. This error may indicate that you’re trying to pass a Tensor to a NumPy call, which is not supported
The notebook worked without problems in the coursera environment.
Any hint on what might be the problem here?