I had download all the file required, and want to see the generated samples from the example_captions; but when I run it on the environment:
linux Ubuntu 14.04.5 LTS (GNU/Linux 3.19.0-25-generic x86_64)
tensorflow 1.3.0
python 2.7
and run using the instruction like sh demo/flowers_demo.sh
and got output and error like:
{
doc_length : 201
filenames : "Data/flowers/example_captions.t7"
queries : "Data/flowers/example_captions.txt"
net_txt : "models/text_encoder/lm_sje_flowers_c10_hybrid_0.00070_1_10_trainvalids.txt_iter16400.t7"
}
Successfully load sentences from: Data/flowers/example_captions.t7
Total number of sentences: 8
num_embeddings: 8 (8, 1024)
2018-05-01 13:06:33.652722: 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.
2018-05-01 13:06:33.652751: 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.
2018-05-01 13:06:33.652760: 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.
2018-05-01 13:06:33.652767: 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.
2018-05-01 13:06:33.652774: 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.
lr_imsize: 64
Traceback (most recent call last):
File "demo/demo.py", line 193, in
build_model(sess, embeddings.shape[-1], batch_size)
File "demo/demo.py", line 68, in build_model
hr_fake_images = model.hr_get_generator(fake_images, hr_c)
File "/home1/y/StackGAN-master/stageII/model.py", line 195, in hr_get_generator
x_c_code = tf.concat(3, [x_code, c_code])
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1061, in concat
dtype=dtypes.int32).get_shape(
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 611, in convert_to_tensor
as_ref=False)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 676, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 121, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 102, in constant
tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 376, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).name))
TypeError: Expected int32, got <prettytensor.pretty_tensor_class.Layer object at 0x7f580cfdba90> of type 'Layer' instead.
and now I had a problem using the prettytensor-0.7.3 occur a error with AttributeError: 'module' object has no attribute 'complex_abs'
how to deal with that?
I had download all the file required, and want to see the generated samples from the example_captions; but when I run it on the environment: linux Ubuntu 14.04.5 LTS (GNU/Linux 3.19.0-25-generic x86_64) tensorflow 1.3.0 python 2.7
and run using the instruction like sh demo/flowers_demo.sh and got output and error like: { doc_length : 201 filenames : "Data/flowers/example_captions.t7" queries : "Data/flowers/example_captions.txt" net_txt : "models/text_encoder/lm_sje_flowers_c10_hybrid_0.00070_1_10_trainvalids.txt_iter16400.t7" } Successfully load sentences from: Data/flowers/example_captions.t7 Total number of sentences: 8 num_embeddings: 8 (8, 1024) 2018-05-01 13:06:33.652722: 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. 2018-05-01 13:06:33.652751: 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. 2018-05-01 13:06:33.652760: 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. 2018-05-01 13:06:33.652767: 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. 2018-05-01 13:06:33.652774: 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. lr_imsize: 64 Traceback (most recent call last): File "demo/demo.py", line 193, in
build_model(sess, embeddings.shape[-1], batch_size)
File "demo/demo.py", line 68, in build_model
hr_fake_images = model.hr_get_generator(fake_images, hr_c)
File "/home1/y/StackGAN-master/stageII/model.py", line 195, in hr_get_generator
x_c_code = tf.concat(3, [x_code, c_code])
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1061, in concat
dtype=dtypes.int32).get_shape(
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 611, in convert_to_tensor
as_ref=False)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 676, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 121, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 102, in constant
tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 376, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).name))
TypeError: Expected int32, got <prettytensor.pretty_tensor_class.Layer object at 0x7f580cfdba90> of type 'Layer' instead.
could anyone help me? Thanks!