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tf.get_embedding_variable stuck in tf.nn.embedding_lookup when ids is negative number #1003

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welsonzhang opened this issue Jul 11, 2024 · 0 comments

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@welsonzhang
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System information

  • OS Platform and Distribution (e.g., Linux Ubuntu 20.04):16.04
  • DeepRec version or commit id: deeprec2208
  • Python version:3.6
  • Bazel version (if compiling from source):
  • GCC/Compiler version (if compiling from source):
  • CUDA/cuDNN version:

Describe the current behavior
when ids is negative number ,embedding_lookup stuck.

Describe the expected behavior
when ids is negative number , embedding_lookup get embedding float list

Code to reproduce the issue

import tensorflow as tf

var = tf.get_embedding_variable("var_0",
                                embedding_dim=3,
                                initializer=tf.ones_initializer(tf.float32),
                                partitioner=tf.fixed_size_partitioner(num_shards=4))

shape = [var1.total_count() for var1 in var]

emb = tf.nn.embedding_lookup(var, tf.cast([0,-1,-2,-5,-6,-7], tf.int64))
fun = tf.multiply(emb, 2.0, name='multiply')
loss = tf.reduce_sum(fun, name='reduce_sum')
opt = tf.train.AdagradOptimizer(0.1)

g_v = opt.compute_gradients(loss)
train_op = opt.apply_gradients(g_v)

init = tf.global_variables_initializer()

sess_config = tf.ConfigProto(allow_soft_placement=True, log_device_placement=False)
with tf.Session(config=sess_config) as sess:
  sess.run([init])
  print(sess.run([emb, train_op, loss]))
  print(sess.run([emb, train_op, loss]))
  print(sess.run([emb, train_op, loss]))
  print(sess.run([shape]))

Provide a reproducible test case that is the bare minimum necessary to generate the problem.

Other info / logs

Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

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