When I tried to run training on MS-COCO dataset,

python data_loader.py --data_set='MS-COCO' --data_dir='MSCOCO-data'

I downloaded the images and captions from [http://mscoco.org/dataset/#download](MS-COCO dataset) The contents of MSCOCO-data/ folder are as follows: MSCOCO-data/ |-- annotations | |-- captions_train2014.json | |-- captions_val2014.json | |-- instances_train2014.json | |-- instances_val2014.json | |-- person_keypoints_train2014.json | |-- person_keypoints_val2014.json |-- meta_train.pkl |-- train2014 | |-- COCO_train2014_000000000009.jpg | |-- COCO_train2014_000000000025.jpg

I got the below error while running the training code:

Traceback (most recent call last):
  File "data_loader.py", line 111, in <module>
    main()
  File "data_loader.py", line 108, in main
    save_caption_vectors_ms_coco(args.data_dir, args.split, args.batch_size)
  File "data_loader.py", line 39, in save_caption_vectors_ms_coco
    h5f_tv_batch = h5py.File( join(data_dir, 'tvs/'+split + '_tvs_' + str(batch_no)), 'w')
  File "/usr/local/lib/python2.7/dist-packages/h5py/_hl/files.py", line 272, in __init__
    fid = make_fid(name, mode, userblock_size, fapl, swmr=swmr)
  File "/usr/local/lib/python2.7/dist-packages/h5py/_hl/files.py", line 98, in make_fid
    fid = h5f.create(name, h5f.ACC_TRUNC, fapl=fapl, fcpl=fcpl)
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper (/tmp/pip-4rPeHA-build/h5py/_objects.c:2684)
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper (/tmp/pip-4rPeHA-build/h5py/_objects.c:2642)
  File "h5py/h5f.pyx", line 96, in h5py.h5f.create (/tmp/pip-4rPeHA-build/h5py/h5f.c:2097)
IOError: Unable to create file (Unable to open file: name = '/home/nitish/mscoco-data/tvs/train_tvs_0', errno = 2, error message = 'no such file or directory', flags = 13, o_flags = 242)

Traceback (most recent call last): File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1628, in _create_c_op c_op = c_api.TF_FinishOperation(op_desc) tensorflow.python.framework.errors_impl.InvalidArgumentError: Dimension 1 in both shapes must be equal, but are 100 and 256. Shapes are [64,100] and [64,256]. From merging shape 0 with other shapes. for 'concat/concat_dim' (op: 'Pack') with input shapes: [64,100], [64,256].

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "train.py", line 238, in main() File "train.py", line 76, in main input_tensors, variables, loss, outputs, checks = gan.build_model() File "/home/bsatya/Study/ML/text-to-image/model.py", line 39, in build_model fake_image = self.generator(t_z, t_real_caption) File "/home/bsatya/Study/ML/text-to-image/model.py", line 139, in generator z_concat = tf.concat(1, [t_z, reduced_text_embedding]) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1121, in concat dtype=dtypes.int32).get_shape().assert_is_compatible_with( File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1050, in convert_to_tensor as_ref=False) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1146, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 971, in _autopacking_conversion_function return _autopacking_helper(v, dtype, name or "packed") File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 923, in _autopacking_helper return gen_array_ops.pack(elems_as_tensors, name=scope) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 4875, in pack "Pack", values=values, axis=axis, name=name) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper op_def=op_def) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func return func(*args, **kwargs) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3274, in create_op op_def=op_def) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1792, in init control_input_ops) File "/home/bsatya/Study/ML/p3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1631, in _create_c_op raise ValueError(str(e)) ValueError: Dimension 1 in both shapes must be equal, but are 100 and 256. Shapes are [64,100] and [64,256]. From merging shape 0 with other shapes. for 'concat/concat_dim' (op: 'Pack') with input shapes: [64,100], [64,256].

There's quite a few directories to create and files to download/extract, and this script makes it easier to get everything set up. For convenience I also created and included a 6.5MB tar.bz of the flower captions.

Hi, here's another question. Here the discriminator's input is wrong image and right text. However according to the original paper (page 5), they use real image and wrong text which is different from your implementation.

Hi, First of all, thanks for your awesome work! I'm wondering that is there any evaluation metrics for this kind of generative model since I want to compare the performance between using Skip Thought Vectors and the other embedding options for captions.

What I did

• Downloaded the pre-trained model
• Created a file (j.caption) with a sample caption
• Ran: python generate_thought_vectors.py --caption_file=j.caption
• Got the following error, any ideas?

['pink flower with green leaves']
Loading model parameters...
Traceback (most recent call last):
  File "generate_thought_vectors.py", line 32, in <module>
    main()
  File "generate_thought_vectors.py", line 23, in main
    model = skipthoughts.load_model()
  File "/Users/jikkujose/Projects/outside_projects/text-to-image/skipthoughts.py", line 38, in load_model
    with open('%s.pkl'%path_to_umodel, 'rb') as f:

Specs

• Mac OSX 10.11.6
• Python 2.7.11

['image_06288.jpg', 'image_08158.jpg', 'image_05755.jpg', 'image_02589.jpg', 'image_07136.jpg', 'image_00386.jpg', 'image_03853.jpg', 'image_02558.jpg', 'image_02394.jpg', 'image_03728.jpg', 'image_00459.jpg', 'image_02971.jpg', 'image_05165.jpg', 'image_00200.jpg', 'image_05604.jpg', 'image_00165.jpg', 'image_06698.jpg', 'image_07523.jpg', 'image_05897.jpg', 'image_00893.jpg', 'image_07566.jpg', 'image_02521.jpg', 'image_02177.jpg', 'image_08017.jpg', 'image_04124.jpg', 'image_01274.jpg', 'image_01322.jpg', 'image_05418.jpg', 'image_03020.jpg', 'image_04845.jpg', 'image_02937.jpg', 'image_04535.jpg', 'image_05900.jpg', 'image_06085.jpg', 'image_01547.jpg', 'image_01584.jpg', 'image_03256.jpg', 'image_04241.jpg', 'image_07573.jpg', 'image_07429.jpg', 'image_05473.jpg', 'image_03866.jpg', 'image_02641.jpg', 'image_02421.jpg', 'image_03829.jpg', 'image_00172.jpg', 'image_04244.jpg', 'image_01564.jpg', 'image_00103.jpg', 'image_00394.jpg', 'image_06692.jpg', 'image_07503.jpg', 'image_02566.jpg', 'image_07964.jpg', 'image_07431.jpg', 'image_04724.jpg', 'image_02230.jpg', 'image_02434.jpg', 'image_05386.jpg', 'image_05502.jpg', 'image_00485.jpg', 'image_04411.jpg', 'image_01350.jpg', 'image_03127.jpg', 'image_06379.jpg', 'image_05504.jpg', 'image_04690.jpg', 'image_06777.jpg', 'image_04227.jpg', 'image_02020.jpg', 'image_03077.jpg', 'image_07699.jpg', 'image_05176.jpg', 'image_03054.jpg', 'image_03833.jpg', 'image_04077.jpg', 'image_04581.jpg', 'image_01178.jpg', 'image_05925.jpg', 'image_04951.jpg', 'image_01707.jpg', 'image_00215.jpg', 'image_00497.jpg', 'image_01570.jpg', 'image_04317.jpg', 'image_04728.jpg', 'image_00960.jpg', 'image_00775.jpg', 'image_05898.jpg', 'image_00606.jpg', 'image_01223.jpg', 'image_03507.jpg', 'image_00898.jpg', 'image_07854.jpg', 'image_05882.jpg', 'image_06700.jpg', 'image_04863.jpg', 'image_01872.jpg', 'image_06113.jpg', 'image_05639.jpg'] 8189 8189 Loading model parameters... Compiling encoders... Loading tables... Traceback (most recent call last): File "data_loader.py", line 110, in main() File "data_loader.py", line 105, in main save_caption_vectors_flowers(args.data_dir) File "data_loader.py", line 76, in save_caption_vectors_flowers model = skipthoughts.load_model() File "/home/sarah/text-to-image/skipthoughts.py", line 60, in load_model utable, btable = load_tables() File "/home/sarah/text-to-image/skipthoughts.py", line 80, in load_tables utable = numpy.load(path_to_tables + 'utable.npy',encoding='latin1') File "/home/sarah/.local/lib/python3.7/site-packages/numpy/lib/npyio.py", line 453, in load pickle_kwargs=pickle_kwargs) File "/home/sarah/.local/lib/python3.7/site-packages/numpy/lib/format.py", line 739, in read_array raise ValueError("Object arrays cannot be loaded when " ValueError: Object arrays cannot be loaded when allow_pickle=False

How can I solve it? Python 3.7 Numpy 1.18.4 Tensorflow 2.2.1 Gast 0.3.3

XXX@XXX:~/codes/python_codes/text-to-image$ python generate_thought_vectors.py --caption_file="Data/sample_captions.txt" ['the flower shown has yellow anther red pistil and bright red petals'] Loading model parameters... Compiling encoders... Loading tables... Traceback (most recent call last): File "generate_thought_vectors.py", line 33, in main() File "generate_thought_vectors.py", line 23, in main model = skipthoughts.load_model() File "/home/tushar/codes/python_codes/text-to-image/skipthoughts.py", line 60, in load_model utable, btable = load_tables() File "/home/tushar/codes/python_codes/text-to-image/skipthoughts.py", line 80, in load_tables utable = numpy.load(path_to_tables + 'utable.npy') File "/usr/local/lib/python2.7/dist-packages/numpy/lib/npyio.py", line 406, in load pickle_kwargs=pickle_kwargs) File "/usr/local/lib/python2.7/dist-packages/numpy/lib/format.py", line 637, in read_array array = pickle.load(fp, **pickle_kwargs) EOFError

Incorporated feedback on https://github.com/paarthneekhara/text-to-image/pull/6 and made some other fixes:

• moved flowers_text_c10.tar.bz2 to Data/
• corrected some extraction paths
• modified README.md to mention new download_datasets.py
• added a requirements.txt

2021-05-26 00:09:24.773721: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found 2021-05-26 00:09:24.781327: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine. WARNING:tensorflow:From C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\compat\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version. Instructions for updating: non-resource variables are not supported in the long term Traceback (most recent call last): File "generate_images.py", line 106, in main() File "generate_images.py", line 64, in main _, _, _, _, _ = gan.build_model() File "C:\Users\Futura Labs\Documents\codes\speechtext_to_image\text-to-image-master\model.py", line 42, in build_model disc_wrong_image, disc_wrong_image_logits = self.discriminator(t_wrong_image, t_real_caption, reuse = True) File "C:\Users\Futura Labs\Documents\codes\speechtext_to_image\text-to-image-master\model.py", line 163, in discriminator h1 = ops.lrelu( self.d_bn1(ops.conv2d(h0, self.options['df_dim']*2, name = 'd_h1_conv'))) #16 File "C:\Users\Futura Labs\Documents\codes\speechtext_to_image\text-to-image-master\Utils\ops.py", line 36, in call ema_apply_op = self.ema.apply([batch_mean, batch_var]) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\training\moving_averages.py", line 469, in apply "Variable", "VariableV2", "VarHandleOp" File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\training\slot_creator.py", line 197, in create_zeros_slot colocate_with_primary=colocate_with_primary) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\training\slot_creator.py", line 174, in create_slot_with_initializer dtype) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\training\slot_creator.py", line 73, in _create_slot_var validate_shape=validate_shape) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1593, in get_variable aggregation=aggregation) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1336, in get_variable aggregation=aggregation) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 591, in get_variable aggregation=aggregation) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 543, in _true_getter aggregation=aggregation) File "C:\pythn\envs\abhin\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 911, in _get_single_variable "reuse=tf.AUTO_REUSE in VarScope?" % name) ValueError: Variable d_bn1/d_bn1_2/moments/Squeeze/ExponentialMovingAverage/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=tf.AUTO_REUSE in VarScope?

ValueError: ('The following error happened while compiling the node', forall_inplace,cpu,encoder__layers}(Elemwise{Maximum}[(0, 0)].0, Elemwise{sub,no_inplace}.0, InplaceDimShuffle{0,1,x}.0, Subtensor{int64:int64:int8}.0, Subtensor{int64:int64:int8}.0, IncSubtensor{InplaceSet;:int64:}.0, encoder_U, encoder_Ux, ScalarFromTensor.0, ScalarFromTensor.0), '\n', 'numpy.ufunc has the wrong size, try recompiling. Expected 192, got 216')

when i run this code, this error occurs. Does anyone konw how to solve it?

Traceback (most recent call last): File "encode_text.py", line 32, in main() File "encode_text.py", line 16, in main model = skipthoughts.load_model() File "/home/anu/Downloads/TAC-GAN-master/skipthoughts.py", line 60, in load_model utable, btable = load_tables() File "/home/anu/Downloads/TAC-GAN-master/skipthoughts.py", line 80, in load_tables utable = numpy.load(path_to_tables + 'utable.npy', encoding='bytes') File "/home/anu/.local/lib/python3.6/site-packages/numpy/lib/npyio.py", line 453, in load pickle_kwargs=pickle_kwargs) File "/home/anu/.local/lib/python3.6/site-packages/numpy/lib/format.py", line 739, in read_array raise ValueError("Object arrays cannot be loaded when " ValueError: Object arrays cannot be loaded when allow_pickle=False how to solve this this

/home/naveen/anaconda3/lib/python3.7/site-packages/dask/config.py:168: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. data = yaml.load(f.read()) or {} WARNING:tensorflow:From /home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.init (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version. Instructions for updating: If using Keras pass *_constraint arguments to layers. (64, 256) Traceback (most recent call last): File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1610, in _create_c_op c_op = c_api.TF_FinishOperation(op_desc) tensorflow.python.framework.errors_impl.InvalidArgumentError: Dimension 1 in both shapes must be equal, but are 100 and 256. Shapes are [64,100] and [64,256]. From merging shape 0 with other shapes. for 'concat/concat_dim' (op: 'Pack') with input shapes: [64,100], [64,256].

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/home/naveen/eclipse-workspace/text-to-image-master/train.py", line 238, in main() File "/home/naveen/eclipse-workspace/text-to-image-master/train.py", line 76, in main input_tensors, variables, loss, outputs, checks = gan.build_model() File "/home/naveen/eclipse-workspace/text-to-image-master/model.py", line 39, in build_model fake_image = self.generator(t_z, t_real_caption) File "/home/naveen/eclipse-workspace/text-to-image-master/model.py", line 141, in generator z_concat = tf.concat(1, [t_z, reduced_text_embedding]) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/util/dispatch.py", line 180, in wrapper return target(*args, **kwargs) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py", line 1427, in concat ops.convert_to_tensor(axis, name="concat_dim",dtype=dtypes.int32).get_shape().assert_has_rank(0) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1184, in convert_to_tensor return convert_to_tensor_v2(value, dtype, preferred_dtype, name) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1242, in convert_to_tensor_v2 as_ref=False) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1296, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py", line 1278, in _autopacking_conversion_function return _autopacking_helper(v, dtype, name or "packed") File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/ops/array_ops.py", line 1214, in _autopacking_helper return gen_array_ops.pack(elems_as_tensors, name=scope) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/ops/gen_array_ops.py", line 6304, in pack "Pack", values=values, axis=axis, name=name) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/op_def_library.py", line 793, in _apply_op_helper op_def=op_def) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func return func(*args, **kwargs) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3360, in create_op attrs, op_def, compute_device) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3429, in _create_op_internal op_def=op_def) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1773, in init control_input_ops) File "/home/naveen/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 1613, in _create_c_op raise ValueError(str(e)) ValueError: Dimension 1 in both shapes must be equal, but are 100 and 256. Shapes are [64,100] and [64,256]. From merging shape 0 with other shapes. for 'concat/concat_dim' (op: 'Pack') with input shapes: [64,100], [64,256].

Write the captions in text file, and save it as Data/sample_captions.txt. Generate the skip thought vectors for these captions using: python generate_thought_vectors.py --caption_file="Data/sample_captions.txt"

When I want to run this code, there is no sample_captions.txt file in the file. I want to know how this is generated. Do you have a generated file to share? @neilsh @paarthneekhara @gitter-badger @AbhishekNarayanan

Traceback (most recent call last): File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\framework\ops.py", line 1628, in _create_c_op c_op = c_api.TF_FinishOperation(op_desc) tensorflow.python.framework.errors_impl.InvalidArgumentError: Dimension 3 in both shapes must be equal, but are 512 and 256. Shapes are [8,4,4,512] and [8,4,4,256]. From merging shape 0 with other shapes. for 'h3_concat/concat_dim' (op: 'Pack') with input shapes: [8,4,4,512], [8,4,4,256].

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "generate_images.py", line 106, in main() File "generate_images.py", line 64, in main _, _, _, _, _ = gan.build_model() File "C:\Users\RanjanNi\Desktop\t2i_skip\Python 3 Codes\model.py", line 39, in build_model disc_real_image, disc_real_image_logits = self.discriminator(t_real_image, t_real_caption) File "C:\Users\RanjanNi\Desktop\t2i_skip\Python 3 Codes\model.py", line 171, in discriminator h3_concat = tf.concat( 3, [h3, tiled_embeddings], name='h3_concat') File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1121, in concat dtype=dtypes.int32).get_shape().assert_is_compatible_with( File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\framework\ops.py", line 1050, in convert_to_tensor as_ref=False) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\framework\ops.py", line 1146, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\ops\array_ops.py", line 971, in _autopacking_conversion_function return _autopacking_helper(v, dtype, name or "packed") File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\ops\array_ops.py", line 923, in _autopacking_helper return gen_array_ops.pack(elems_as_tensors, name=scope) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 5856, in pack "Pack", values=values, axis=axis, name=name) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper op_def=op_def) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func return func(*args, **kwargs) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\framework\ops.py", line 3274, in create_op op_def=op_def) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\framework\ops.py", line 1792, in init control_input_ops) File "C:\Users\RanjanNi\AppData\Local\Continuum\anaconda3\envs\py36\lib\site-packages\tensorflow\python\framework\ops.py", line 1631, in _create_c_op raise ValueError(str(e)) ValueError: Dimension 3 in both shapes must be equal, but are 512 and 256. Shapes are [8,4,4,512] and [8,4,4,256]. From merging shape 0 with other shapes. for 'h3_concat/concat_dim' (op: 'Pack') with input shapes: [8,4,4,512], [8,4,4,256].