I have a problem to load pretrained params in tensorlayer.
I try to use srgan (https://github.com/tensorlayer/srgan) and its pretrained params (https://github.com/tensorlayer/srgan/releases/tag/1.2.0)
Applicable code is below
G = get_G([1, None, None, 3])
load_params = tl.files.load_npz(path='', name='g_srgan.npz')
tl.files.assign_weights(load_params,
#G.load_weights(os.path.join("g_srgan.npz"))
G.eval()
I got error:
Traceback (most recent call last):
File "train.py", line 194, in <module>
evaluate(session)
File "train.py", line 156, in evaluate
tl.files.assign_weights(load_params, G)
File "/usr/local/lib/python3.6/dist-packages/tensorlayer/files/utils.py", line 2023, in assign_weights
ops.append(network.all_weights[idx].assign(param))
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/resource_variable_ops.py", line 819, in assign
self._shape.assert_is_compatible_with(value_tensor.shape)
File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/tensor_shape.py", line 1110, in assert_is_compatible_with
raise ValueError("Shapes %s and %s are incompatible" % (self, other))
ValueError: Shapes (1, 1, 1, 64) and (64,) are incompatible
Please tell me the solution.
Thanks !!
Related
error is：
Traceback (most recent call last):
File "C:\Users\DH\PycharmProjects\four\model_test.py", line 53, in
movie_combine_layer_flat_val = movie_layer_model([np.reshape(item.take(0), [1, 1]), titles, actors, categories])
File "C:\Users\DH\anaconda3\envs\test\lib\site-packages\keras\utils\traceback_utils.py", line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
File "C:\Users\DH\AppData\Roaming\Python\Python39\site-packages\tensorflow\python\framework\ops.py", line 7215, in raise_from_not_ok_status
raise core._status_to_exception(e) from None # pylint: disable=protected-access
tensorflow.python.framework.errors_impl.InvalidArgumentError: Exception encountered when calling layer "movie_actor_embed_layer" " f"(type Embedding).
{{function_node _wrapped__ResourceGather_device/job:localhost/replica:0/task:0/device:CPU:0}} indices[0,3] = 2010 is not in [0, 2006) [Op:ResourceGather]
Call arguments received by layer "movie_actor_embed_layer" " f"(type Embedding):
• inputs=tf.Tensor(shape=(1, 30), dtype=int32)
can run machine is tensorflow-gpu-2.6, error is tensorflow-cpu-2.6, does that matter?
Traceback (most recent call last): File
"AutoFC_AlexNet_randomsearch_CalTech101_v2.py", line 112, in
X = layers.Dense(neurons, activation=activation, kernel_initializer=weight_init)(X) File
"/home/shabbeer/NAS/lib/python3.5/site-packages/keras/legacy/interfaces.py",
line 91, in wrapper
return func(*args, **kwargs) File "/home/shabbeer/NAS/lib/python3.5/site-packages/keras/layers/core.py",
line 824, in init
self.kernel_initializer = initializers.get(kernel_initializer) File
"/home/shabbeer/NAS/lib/python3.5/site-packages/keras/initializers.py",
line 503, in get
identifier) ValueError: ('Could not interpret initializer identifier:', 0.2)
I am getting the above error when running the code using tensorflow-gpu version 1.4.0 and keras version 2.1.3
you should change it to X = layers.Dense(neurons, activation=activation, kernel_initializer=keras.initializers.Constant(weight_init))(X)
I am actually working with miniconda and tensorflow and trying to train a model for object detection and I'm facing a problem when running generate_ tfrecord.py to convert csv to tfrecord the error is:
"generate_tfrecord.py", line 90, in <module>
tf.app.run()
I used this link
https://github.com/datitran/raccoon_dataset/blob/master/generate_tfrecord.py
(tensorflow) C:\Users\OctaNet\Miniconda3\envs\tensorflow\models\research\object_detection>python generate_tfrecord.py --csv_input=images/train.csv --output_path=data/train.record --image_dir=images/train/
Iterating train
Traceback (most recent call last):
File "generate_tfrecord.py", line 90, in <module>
tf.app.run()
File "C:\Users\OctaNet\Miniconda3\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
_sys.exit(main(argv))
File "generate_tfrecord.py", line 80, in main
tf_example = create_tf_example(group, path)
File "generate_tfrecord.py", line 67, in create_tf_example
'image/object/class/label': dataset_util.int64_list_feature(classes),
File "C:\Users\OctaNet\Miniconda3\envs\tensorflow\lib\site-packages\object_detection-0.1-py3.6.egg\object_detection\utils\dataset_util.py", line 26, in int64_list_feature
return tf.train.Feature(int64_list=tf.train.Int64List(value=value))
TypeError: None has type NoneType, but expected one of: int, long
can someone explain why tensorflow is giving me trouble when running the following code.
import tensorflow as tf
x = tf.keras.layers.Input(shape=(1,))
y = tf.keras.layers.Dense(1, activation=tf.nn.relu)(x)
loss = tf.losses.mean_squared_error(x,y)
grad = tf.gradients(loss, tf.trainable_variables())
# !!! GIVES ME TROUBLE !!!
clipped_grad = tf.clip_by_norm(grad, 1.0)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
sess.run(y, feed_dict={x: [[1.0], [2.0], [3.0]]})
The error I get:
Traceback (most recent call last):
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\framework\ops.py", line 1589, in _create_c_op
c_op = c_api.TF_FinishOperation(op_desc)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shapes must be equal rank, but are 2 and 1
From merging shape 0 with other shapes. for 'clip_by_norm/t' (op: 'Pack') with input shapes: [1,1], [1].
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/TObs/.PyCharmCE2018.1/config/scratches/scratch.py", line 11, in <module>
clipped_grad = tf.clip_by_norm(grad, 1.0)
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\ops\clip_ops.py", line 140, in clip_by_norm
t = ops.convert_to_tensor(t, name="t")
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\framework\ops.py", line 1011, in convert_to_tensor
as_ref=False)
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\framework\ops.py", line 1107, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\ops\array_ops.py", line 960, in _autopacking_conversion_function
return _autopacking_helper(v, inferred_dtype, name or "packed")
File "D:\Program Files\Python\Python_3_6_2\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 "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 5532, in pack
"Pack", values=values, axis=axis, name=name)
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\framework\ops.py", line 3414, in create_op
op_def=op_def)
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\framework\ops.py", line 1756, in __init__
control_input_ops)
File "D:\Program Files\Python\Python_3_6_2\lib\site-packages\tensorflow\python\framework\ops.py", line 1592, in _create_c_op
raise ValueError(str(e))
ValueError: Shapes must be equal rank, but are 2 and 1
From merging shape 0 with other shapes. for 'clip_by_norm/t' (op: 'Pack') with input shapes: [1,1], [1].
Any thoughts? Im running on a Windows10 machine, with tensorflow-gpu 1.9.0, NVidia GTX 1080.
Help would be much appreciated :)
Cheers,
Tobs.
so after tinkering around I found out that one have to apply the tf.clip_by_norm seperatly for each value in the gradients tensor liek so:
clipped_gradients = [tf.clip_by_norm(g, grad_norm_clip) for g in tf.gradients(loss, tf.trainable_variables())]
I guess, thats the right way to do, right?
Cheers,
Tobs.
I try to train NASNet-A_Mobile_224 for two class classification by using train_image_classifier.py from slim with nasnet_mobile, However I get error
TypeError: separable_convolution2d() got an unexpected keyword argument 'data_format'
I suspect that the new NASNet requires TF version 1.4. Can somebody confirm this? I'm using Tensorflow 1.3.
More extensive error is given below:
Traceback (most recent call last):
File "train_image_classifier.py", line 574, in <module>
tf.app.run()
File "/home/sami/virenv/tensorflow_vanilla/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "train_image_classifier.py", line 474, in main
clones = model_deploy.create_clones(deploy_config, clone_fn, [batch_queue])
File "/home/sami/projects/Tools/models/research/slim/deployment/model_deploy.py", line 193, in create_clones
outputs = model_fn(*args, **kwargs)
File "train_image_classifier.py", line 457, in clone_fn
logits, end_points = network_fn(images)
File "/home/sami/projects/Tools/models/research/slim/nets/nets_factory.py", line 135, in network_fn
return func(images, num_classes, is_training=is_training, **kwargs)
File "/home/sami/projects/Tools/models/research/slim/nets/nasnet/nasnet.py", line 371, in build_nasnet_mobile
final_endpoint=final_endpoint)
File "/home/sami/projects/Tools/models/research/slim/nets/nasnet/nasnet.py", line 450, in _build_nasnet_base
net, cell_outputs = stem()
File "/home/sami/projects/Tools/models/research/slim/nets/nasnet/nasnet.py", line 445, in <lambda>
stem = lambda: _imagenet_stem(images, hparams, stem_cell)
File "/home/sami/projects/Tools/models/research/slim/nets/nasnet/nasnet.py", line 264, in _imagenet_stem
cell_num=cell_num)
File "/home/sami/projects/Tools/models/research/slim/nets/nasnet/nasnet_utils.py", line 326, in __call__
stride, original_input_left)
File "/home/sami/projects/Tools/models/research/slim/nets/nasnet/nasnet_utils.py", line 352, in _apply_conv_operation
net = _stacked_separable_conv(net, stride, operation, filter_size)
File "/home/sami/projects/Tools/models/research/slim/nets/nasnet/nasnet_utils.py", line 183, in _stacked_separable_conv
stride=stride)
File "/home/sami/virenv/tensorflow_vanilla/local/lib/python2.7/site-packages/tensorflow/contrib/framework/python/ops/arg_scope.py", line 181, in func_with_args
return func(*args, **current_args)
TypeError: separable_convolution2d() got an unexpected keyword argument 'data_format'
YES,it must be tensorflow 1.4.0