What is the equivalent cpp function for tf.train.import_meta_graph() in tensorflow?
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About “What is the equivalent cpp function for tf.train.import_meta_graph() in tensorflow?” questions
I need to know the equivalent C++ function for https://www.tensorflow.org/api_docs/python/tf/train/import_meta_graph
Can anyone please help with it?
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Let's say I have a 2 x 3 matrix and I want to create a 6 x 2 x 3 matrix where each element in the first dimension is the original 2 x 3 matrix.
In PyTorch, I can do this:
import torch
from torch.
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I am wondering if there is any equivalent to
theano.function(inputs=[x,y], # list of input variables
outputs=..., # what values to be returned
updates=..., # “state” values to be modified
givens=...
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I'm wonder wrt this topic
I want to resolve update issue in Theano.function with this lazy tensorflow constrution:
class TensorFlowTheanoFunction(object):
def __init__(self, inputs, outputs, sess...
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I am trying to improve the performance of our api which uses a model written in tensorflow. I have identified the line which is taking up to ten seconds to execute when multiple processes are execu...
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I am trying to improve the performance of our api which uses a model written in tensorflow. I have identified the line which is taking up to ten seconds to execute when multiple processes are execu...
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I serialized a Tensorflow model with the following code ...
save_path = self.saver.save(self.session, os.path.join(self.logdir, "model.ckpt"), global_step)
logging.info("Model saved in file: %s" %
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I cannot find the equivalent of numpy's fill function in Tensorflow. Tensorflow has a fill function, but it is not equivalent. Specifically, the tensorflow function returns a new, constant tensor. ...
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Following the MNIST for ML beginners in TensorFlow, we learn the most basic SGD with learning rate 0.5, batch size 100 and 1000 steps like this
train_step = tf.train.GradientDescentOptimizer(0.5).
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As stated in the title, is there a TensorFlow equivalent of the numpy.all() function to check if all the values in a bool tensor are True? What is the best way to implement such a check?
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