hi, I use: Tensorflow V 1.10 CPU version Tensorlayer V 1.10.1 python 3.6 windows 10

after run : python main.py I get ValueError

Traceback (most recent call last): File "c:/Users/USER/Desktop/פרוייקט תואר שני/playgroung/dcgan/main.py", line 166, in tf.app.run() File "C:\Python\3.6\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run _sys.exit(main(argv)) File "c:/Users/USER/Desktop/פרוייקט תואר שני/playgroung/dcgan/main.py", line 59, in main _, d2_logits = discriminator(real_images, is_train=True, reuse=True) File "c:\Users\USER\Desktop\פרוייקט תואר שני\playgroung\dcgan\model.py", line 81, in discriminator W_init = w_init, name='d/h4/lin_sigmoid') File "c:\Users\USER\Desktop\פרוייקט תואר שני\playgroung\dcgan\tensorlayer\layers\core.py", line 926, in init W = tf.get_variable(name='W', shape=(n_in, n_units), initializer=W_init, dtype=LayersConfig.tf_dtype, **W_init_args) File "C:\Python\3.6\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1467, in get_variable aggregation=aggregation) File "C:\Python\3.6\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1217, in get_variable aggregation=aggregation) File "C:\Python\3.6\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 527, in get_variable aggregation=aggregation) File "C:\Python\3.6\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 481, in _true_getter aggregation=aggregation) File "C:\Python\3.6\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 853, in _get_single_variable found_var.get_shape())) ValueError: Trying to share variable discriminator/d/h4/lin_sigmoid/W, but specified shape (8192, 1) and found shape (2048, 1).

Tried twice, same error.

python download.py celebA
./data/img_align_celeba.zip: 25.5kB [12:15, 34.7B/s]Traceback (most recent call last):
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/urllib3/response.py", line 302, in _error_catcher
    yield
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/urllib3/response.py", line 601, in read_chunked
    chunk = self._handle_chunk(amt)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/urllib3/response.py", line 557, in _handle_chunk
    value = self._fp._safe_read(amt)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/http/client.py", line 614, in _safe_read
    raise IncompleteRead(b''.join(s), amt)
http.client.IncompleteRead: IncompleteRead(5887 bytes read, 26881 more expected)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/requests/models.py", line 745, in generate
    for chunk in self.raw.stream(chunk_size, decode_content=True):
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/urllib3/response.py", line 432, in stream
    for line in self.read_chunked(amt, decode_content=decode_content):
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/urllib3/response.py", line 626, in read_chunked
    self._original_response.close()
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/contextlib.py", line 99, in __exit__
    self.gen.throw(type, value, traceback)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/urllib3/response.py", line 320, in _error_catcher
    raise ProtocolError('Connection broken: %r' % e, e)
urllib3.exceptions.ProtocolError: ('Connection broken: IncompleteRead(5887 bytes read, 26881 more expected)', IncompleteRead(5887 bytes read, 26881 more expected))

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "download.py", line 164, in <module>
    download_celeb_a('./data')
  File "download.py", line 91, in download_celeb_a
    download_file_from_google_drive(drive_id, save_path)
  File "download.py", line 56, in download_file_from_google_drive
    save_response_content(response, destination)
  File "download.py", line 68, in save_response_content
    unit='B', unit_scale=True, desc=destination):
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/tqdm/_tqdm.py", line 962, in __iter__
    for obj in iterable:
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/requests/models.py", line 748, in generate
    raise ChunkedEncodingError(e)
requests.exceptions.ChunkedEncodingError: ('Connection broken: IncompleteRead(5887 bytes read, 26881 more expected)', IncompleteRead(5887 bytes read, 26881 more expected))

Trying to run main.py and I get the following error.

traceback (most recent call last):
  File "main.py", line 23, in <module>
    flags.DEFINE_integer("train_size", np.inf, "The size of train images [np.inf]")
  File "/anaconda2/lib/python2.7/site-packages/tensorflow/python/platform/flags.py", line 58, in wrapper
    return original_function(*args, **kwargs)
  File "/anaconda2/lib/python2.7/site-packages/absl/flags/_defines.py", line 315, in DEFINE_integer
    DEFINE(parser, name, default, help, flag_values, serializer, **args)
  File "/anaconda2/lib/python2.7/site-packages/absl/flags/_defines.py", line 81, in DEFINE
    DEFINE_flag(_flag.Flag(parser, serializer, name, default, help, **args),
  File "/anaconda2/lib/python2.7/site-packages/absl/flags/_flag.py", line 107, in __init__
    self._set_default(default)
  File "/anaconda2/lib/python2.7/site-packages/absl/flags/_flag.py", line 196, in _set_default
    self.default = self._parse(value)
  File "/anaconda2/lib/python2.7/site-packages/absl/flags/_flag.py", line 169, in _parse
    'flag --%s=%s: %s' % (self.name, argument, e))
absl.flags._exceptions.IllegalFlagValueError: flag --train_size=inf: Expect argument to be a string or int, found <type 'float'>

Has anyone else encountered this?

Running train.py i get the following error:

Traceback (most recent call last):
  File "train.py", line 60, in <module>
    train()
  File "train.py", line 44, in train
    grad = tape.gradient(g_loss, G.trainable_weights)
AttributeError: 'Model' object has no attribute 'trainable_weights'

am i running a wrong version of tensorflow/tensorlayer (2.0.0a0/2.0.0)?

The url for CelebA dataset in download.py dose not work now because of the dropbox problem. So It's better to change it to the url of google-drive or baidu-drive.

• Added a mini-batch generator function.
• Renamed generator and discriminator functions.
• Removed logits from generator as it was redundant.
• Changed w_init in both models to tf.glorot_normal_initializer since it has shown to improve convergence of model.
• Using imageio instead of scipy.misc wherever possible since it is deprecated.

• Made code compatible with TL1.10.1 and TF1.10.0.
• Removed out size and batch_size from DeConv2D layers since they're no longer needed.
• Replaced tl.act.lrelu with tf.nn.leaky_relu since former is deprecated.
• Replaced tl.layers.initialize_global_variables with tf.global_variables_initializer since former is deprecated.
• Changed flag train_size dtype from int to float due to an error.
• Impoved code readability and removed redundant comments and code.
• Removed pprint in favour of custom logging the flags since pprint was'nt able to access flag values.
• Fixed wildcard imports and removed unused ones.
• Updated main module doc.
• Removed tensorlayer package from root dir since it is installed on system.

Note: Fixes #9 and #12.

When I pass --sample_size 256 as a flag to main.py, I get

ValueError: Cannot feed value of shape (256, 100) for Tensor 'z_noise:0', which has shape '(64, 100)'

When I pass --sample_size 256 and --batch_size 256, the code went into an endless loop just saying "Sample images updated!" without running each epoch.

Hello! I've found a performance issue in /data.py: ds.batch(batch_size)(here) should be called before ds.map(_map_fn, num_parallel_calls=4)(here), which could make your program more efficient.

Here is the tensorflow document to support it.

Besides, you need to check the function _map_fn called in ds.map(_map_fn, num_parallel_calls=4) whether to be affected or not to make the changed code work properly. For example, if _map_fn needs data with shape (x, y, z) as its input before fix, it would require data with shape (batch_size, x, y, z) after fix.

Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.

I would like to train on an existing saved checkpoint but it seems the GAN learn from scratches.

Is there some way to load a existing checkpoint ?

Thanks in advance.

I have this error! can you help me, please?

WARNING: Logging before flag parsing goes to stderr. I0718 14:45:17.243686 140030963623808 tl_logging.py:99] [!] checkpoint exists ... I0718 14:45:17.247771 140030963623808 tl_logging.py:99] [!] samples exists ... W0718 14:45:19.318463 140030963623808 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/data/ops/dataset_ops.py:505: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version. Instructions for updating: tf.py_func is deprecated in TF V2. Instead, there are two options available in V2. - tf.py_function takes a python function which manipulates tf eager tensors instead of numpy arrays. It's easy to convert a tf eager tensor to an ndarray (just call tensor.numpy()) but having access to eager tensors means tf.py_functions can use accelerators such as GPUs as well as being differentiable using a gradient tape. - tf.numpy_function maintains the semantics of the deprecated tf.py_func (it is not differentiable, and manipulates numpy arrays). It drops the stateful argument making all functions stateful.

I0718 14:45:19.464441 140030963623808 tl_logging.py:99] Input _inputlayer_1: [None, 100] I0718 14:45:19.974161 140030963623808 tl_logging.py:99] Dense dense_1: 8192 No Activation I0718 14:45:20.649731 140030963623808 tl_logging.py:99] Reshape reshape_1 I0718 14:45:20.707117 140030963623808 tl_logging.py:99] BatchNorm batchnorm_1: decay: 0.900000 epsilon: 0.000010 act: relu is_train: False I0718 14:45:20.782280 140030963623808 tl_logging.py:99] DeConv2d deconv2d_1: n_filters: 256 strides: (2, 2) padding: SAME act: No Activation dilation: (1, 1) I0718 14:45:22.796400 140030963623808 tl_logging.py:99] BatchNorm batchnorm2d_1: decay: 0.900000 epsilon: 0.000010 act: relu is_train: False I0718 14:45:22.873876 140030963623808 tl_logging.py:99] DeConv2d deconv2d_2: n_filters: 128 strides: (2, 2) padding: SAME act: No Activation dilation: (1, 1) I0718 14:45:23.076492 140030963623808 tl_logging.py:99] BatchNorm batchnorm2d_2: decay: 0.900000 epsilon: 0.000010 act: relu is_train: False I0718 14:45:23.153287 140030963623808 tl_logging.py:99] DeConv2d deconv2d_3: n_filters: 64 strides: (2, 2) padding: SAME act: No Activation dilation: (1, 1) I0718 14:45:23.227763 140030963623808 tl_logging.py:99] BatchNorm batchnorm2d_3: decay: 0.900000 epsilon: 0.000010 act: relu is_train: False I0718 14:45:23.307783 140030963623808 tl_logging.py:99] DeConv2d deconv2d_4: n_filters: 3 strides: (2, 2) padding: SAME act: tanh dilation: (1, 1) I0718 14:45:23.390201 140030963623808 tl_logging.py:99] Input _inputlayer_2: [None, 64, 64, 3] I0718 14:45:23.456669 140030963623808 tl_logging.py:99] Conv2d conv2d_1: n_filter: 64 filter_size: (5, 5) strides: (2, 2) pad: SAME act: I0718 14:45:23.530629 140030963623808 tl_logging.py:99] Conv2d conv2d_2: n_filter: 128 filter_size: (5, 5) strides: (2, 2) pad: SAME act: No Activation I0718 14:45:23.608061 140030963623808 tl_logging.py:99] BatchNorm batchnorm2d_4: decay: 0.900000 epsilon: 0.000010 act: is_train: False I0718 14:45:23.691769 140030963623808 tl_logging.py:99] Conv2d conv2d_3: n_filter: 256 filter_size: (5, 5) strides: (2, 2) pad: SAME act: No Activation I0718 14:45:23.775271 140030963623808 tl_logging.py:99] BatchNorm batchnorm2d_5: decay: 0.900000 epsilon: 0.000010 act: is_train: False I0718 14:45:23.942049 140030963623808 tl_logging.py:99] Conv2d conv2d_4: n_filter: 512 filter_size: (5, 5) strides: (2, 2) pad: SAME act: No Activation I0718 14:45:24.041154 140030963623808 tl_logging.py:99] BatchNorm batchnorm2d_6: decay: 0.900000 epsilon: 0.000010 act: is_train: False I0718 14:45:24.114703 140030963623808 tl_logging.py:99] Flatten flatten_1: I0718 14:45:24.177696 140030963623808 tl_logging.py:99] Dense dense_2: 1 identity I0718 14:45:29.721007 140030963623808 tl_logging.py:99] [*] Saving TL weights into checkpoint/G.npz I0718 14:45:31.268130 140030963623808 tl_logging.py:99] [*] Saved I0718 14:45:31.274845 140030963623808 tl_logging.py:99] [*] Saving TL weights into checkpoint/D.npz I0718 14:45:32.590787 140030963623808 tl_logging.py:99] [*] Saved

UnboundLocalError Traceback (most recent call last) in () 58 59 if name == 'main': ---> 60 train()

in train() 53 D.save_weights('{}/D.npz'.format(flags.checkpoint_dir), format='npz') 54 G.eval() ---> 55 result = G(z) 56 G.train() 57 tl.visualize.save_images(result.numpy(), [num_tiles, num_tiles], '{}/train_{:02d}.png'.format(flags.sample_dir, epoch))

UnboundLocalError: local variable 'z' referenced before assignment

Tried both the dcgan folder version of tensorlayer (1.4.5) and installed version of tensorlayer (1.8.1). tensorflow version is 1.6.0.

$ python main.py 
/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
Traceback (most recent call last):
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_flag.py", line 166, in _parse
    return self.parser.parse(argument)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_argument_parser.py", line 152, in parse
    val = self.convert(argument)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_argument_parser.py", line 268, in convert
    type(argument)))
TypeError: Expect argument to be a string or int, found <class 'float'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "main.py", line 23, in <module>
    flags.DEFINE_integer("train_size", np.inf, "The size of train images [np.inf]")
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/tensorflow/python/platform/flags.py", line 58, in wrapper
    return original_function(*args, **kwargs)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_defines.py", line 315, in DEFINE_integer
    DEFINE(parser, name, default, help, flag_values, serializer, **args)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_defines.py", line 81, in DEFINE
    DEFINE_flag(_flag.Flag(parser, serializer, name, default, help, **args),
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_flag.py", line 107, in __init__
    self._set_default(default)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_flag.py", line 196, in _set_default
    self.default = self._parse(value)
  File "/home/ly/anaconda3/envs/learning/lib/python3.6/site-packages/absl/flags/_flag.py", line 169, in _parse
    'flag --%s=%s: %s' % (self.name, argument, e))
absl.flags._exceptions.IllegalFlagValueError: flag --train_size=inf: Expect argument to be a string or int, found <class 'float'>