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H13-311_V3.5 · Question #89

None of the following options TensorFlow2.0. The supported operators are:

The correct answer is C. ^. Option C (^) is the unsupported operator because in Python, ^ is the bitwise XOR operator - not exponentiation - and TensorFlow 2.0 does not overload it for tensor operations, so using it will raise a TypeError. The distractors are wrong because TensorFlow 2.0 does support all…

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Question

None of the following options TensorFlow2.0. The supported operators are:

Options

  • Apow
  • B@
  • C^
  • D//

How the community answered

(48 responses)
  • A
    6% (3)
  • B
    4% (2)
  • C
    77% (37)
  • D
    13% (6)

Explanation

Option C (^) is the unsupported operator because in Python, ^ is the bitwise XOR operator - not exponentiation - and TensorFlow 2.0 does not overload it for tensor operations, so using it will raise a TypeError.

The distractors are wrong because TensorFlow 2.0 does support all three of them: pow (A) is supported via tf.pow() and the ** operator; @ (B) is the PEP 465 matrix multiplication operator, which TF2 maps to tf.linalg.matmul; and // (D) is the floor division operator, also overloaded for tensors.

Memory tip: The trap is assuming ^ means "to the power of" - it does in math notation, but in Python it's XOR. Ask yourself: "Does TF need to support XOR on tensors?" - not as a standard arithmetic operator, so it's the odd one out.

Topics

#TensorFlow operators#Python operators#API support#operator compatibility

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