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Since the environment is different as follows I changed some options.
[environment]
CentOS 17.4
tensorflow-gpu 2.0.0
CUDA 10.0
CUDNN7.4.2
gcc8.3.2
By using tf_upgrade_v2, test_forward_ASL.py run and I can the test_forward_ASL.py
However, when I run test_gradient_ASL.py
I firstly met following error. Warning]WARNING:tensorflow:From test_gradient_ASL-TF20.py:45: compute_gradient_error (from tensorflow.python.ops.gradient_checker) is deprecated and will be removed in a future version. Instructions for updating: Use tf.test.compute_gradient in 2.0, which has better support for functions. Note that the two versions have different usage, so code change is needed.
[compile Errror] for code line 45, 73,
Attribute Error err = gradient_checker.compute_gradient_error(a, arr.shape, result, result.get_shape().as_list(), x_init_value=arr)
err = gradient_checker.compute_gradient_error(c, shift.shape,result, result.get_shape().as_list(), x_init_value=shift)
AttributeError: Tensor.graph is meaningless when eager execution is enabled. Thus I changed gradient_checker.compute_gradient_error function like below.
However, I met another error
Traceback (most recent call last): File "", line 54, in active_shift2d_op tensorflow.python.eager.core._FallbackException: Expecting int64_t value for attr strides, got tensorflow.python.framework.ops.EagerTensor
TypeError: Expected list for 'strides' argument to 'active_shift2d_op' Op, not .
library file is made by c++, thus it has int64_t data type, however tensorflow doesn't have int64_t type.
How can I resolve the error by removing type difference?
Thank you in advance~
The text was updated successfully, but these errors were encountered:
Since the environment is different as follows I changed some options.
[environment]
CentOS 17.4
tensorflow-gpu 2.0.0
CUDA 10.0
CUDNN7.4.2
gcc8.3.2
By using tf_upgrade_v2, test_forward_ASL.py run and I can the test_forward_ASL.py
However, when I run test_gradient_ASL.py
I firstly met following error. Warning]WARNING:tensorflow:From test_gradient_ASL-TF20.py:45: compute_gradient_error (from tensorflow.python.ops.gradient_checker) is deprecated and will be removed in a future version. Instructions for updating: Use tf.test.compute_gradient in 2.0, which has better support for functions. Note that the two versions have different usage, so code change is needed.
[compile Errror] for code line 45, 73,
Attribute Error err = gradient_checker.compute_gradient_error(a, arr.shape, result, result.get_shape().as_list(), x_init_value=arr)
err = gradient_checker.compute_gradient_error(c, shift.shape,result, result.get_shape().as_list(), x_init_value=shift)
AttributeError: Tensor.graph is meaningless when eager execution is enabled. Thus I changed gradient_checker.compute_gradient_error function like below.
However, I met another error
Traceback (most recent call last): File "", line 54, in active_shift2d_op tensorflow.python.eager.core._FallbackException: Expecting int64_t value for attr strides, got tensorflow.python.framework.ops.EagerTensor
TypeError: Expected list for 'strides' argument to 'active_shift2d_op' Op, not .
library file is made by c++, thus it has int64_t data type, however tensorflow doesn't have int64_t type.
How can I resolve the error by removing type difference?
Thank you in advance~
The text was updated successfully, but these errors were encountered: