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Results 1 - 4 of 4 for dst_input (0.3 sec)

  1. tensorflow/c/c_api.cc

    }
    
    void TF_OperationAllInputs(TF_Operation* oper, TF_Output* inputs,
                               int max_inputs) {
      for (auto* edge : oper->node.in_edges()) {
        if (edge->dst_input() >= 0 && edge->dst_input() < max_inputs) {
          inputs[edge->dst_input()] = {ToOperation(edge->src()),
                                       edge->src_output()};
        }
      }
    }
    
    int TF_OperationOutputNumConsumers(TF_Output oper_out) {
    Registered: Tue Nov 05 12:39:12 UTC 2024
    - Last Modified: Sat Oct 12 16:27:48 UTC 2024
    - 102.3K bytes
    - Viewed (0)
  2. configure.py

    def is_ppc64le():
      return platform.machine() == 'ppc64le'
    
    
    def is_s390x():
      return platform.machine() == 's390x'
    
    
    def is_cygwin():
      return platform.system().startswith('CYGWIN_NT')
    
    
    def get_input(question):
      try:
        try:
          answer = raw_input(question)
        except NameError:
          answer = input(question)  # pylint: disable=bad-builtin
      except EOFError:
        answer = ''
      return answer
    
    
    Registered: Tue Nov 05 12:39:12 UTC 2024
    - Last Modified: Wed Oct 02 22:16:02 UTC 2024
    - 48.2K bytes
    - Viewed (0)
  3. guava/src/com/google/common/io/ByteStreams.java

    import com.google.common.math.IntMath;
    import com.google.errorprone.annotations.CanIgnoreReturnValue;
    import java.io.ByteArrayInputStream;
    import java.io.ByteArrayOutputStream;
    import java.io.DataInput;
    import java.io.DataInputStream;
    import java.io.DataOutput;
    import java.io.DataOutputStream;
    import java.io.EOFException;
    import java.io.FilterInputStream;
    import java.io.IOException;
    import java.io.InputStream;
    Registered: Fri Nov 01 12:43:10 UTC 2024
    - Last Modified: Sat Oct 19 00:26:48 UTC 2024
    - 29.7K bytes
    - Viewed (0)
  4. RELEASE.md

    `tf.split(value, num_or_size_splits, axis)`. * `tf.sparse_split` now takes
    arguments in reversed order and with different keywords. In particular we now
    match NumPy order as `tf.sparse_split(sp_input, num_split, axis)`. NOTE: we have
    temporarily made `tf.sparse_split` require keyword arguments. * `tf.concat` now
    takes arguments in reversed order and with different keywords. In particular we
    Registered: Tue Nov 05 12:39:12 UTC 2024
    - Last Modified: Tue Oct 22 14:33:53 UTC 2024
    - 735.3K bytes
    - Viewed (0)
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