Hi! I've tried to run your code, it works well with iNetwork.py, but have an issue with neural_doodle.py(improved_neural_doodle.py the same). The problem is:
Using TensorFlow backend.
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:458: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:459: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:460: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:461: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:462: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:465: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
2020-09-09 09:51:55.177770: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2020-09-09 09:51:55.177823: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2020-09-09 09:51:55.177835: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2020-09-09 09:51:55.177844: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2020-09-09 09:51:55.177854: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
File "/content/Neural-Style-Transfer/improved_neural_doodle.py", line 301, in <module>
sl = style_loss(style_feat, target_feat, style_masks, target_masks)
File "/content/Neural-Style-Transfer/improved_neural_doodle.py", line 267, in style_loss
loss += region_style_weight * region_style_loss(style_image, target_image, style_mask, target_mask)
File "/content/Neural-Style-Transfer/improved_neural_doodle.py", line 248, in region_style_loss
s = gram_matrix(masked_style) / K.mean(style_mask) / nb_channels
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py", line 829, in binary_op_wrapper
y = ops.convert_to_tensor(y, dtype=x.dtype.base_dtype, name="y")
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 676, in convert_to_tensor
as_ref=False)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 741, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 614, in _TensorTensorConversionFunction
% (dtype.name, t.dtype.name, str(t)))
### **ValueError: Tensor conversion requested dtype float32 for Tensor with dtype int32: 'Tensor("strided_slice_8:0", shape=(), dtype=int32)**
Hi! I've tried to run your code, it works well with iNetwork.py, but have an issue with neural_doodle.py(improved_neural_doodle.py the same). The problem is:
and ValueError:
What should I do to fix it?