[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.Equal\n\n\u003cbr /\u003e\n\nReturns the truth value of (x == y) element-wise.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.Equal`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Equal)\n\n\u003cbr /\u003e\n\n tf.raw_ops.Equal(\n x, y, incompatible_shape_error=True, name=None\n )\n\n**Note:** `Equal` supports broadcasting. More about broadcasting [here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html) \n\n x = tf.constant([2, 4])\n y = tf.constant(2)\n tf.math.equal(x, y) ==\u003e array([True, False])\n\n x = tf.constant([2, 4])\n y = tf.constant([2, 4])\n tf.math.equal(x, y) ==\u003e array([True, True])\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------------------|---------------------------------------------|\n| `x` | A `Tensor`. |\n| `y` | A `Tensor`. Must have the same type as `x`. |\n| `incompatible_shape_error` | An optional `bool`. Defaults to `True`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `bool`. ||\n\n\u003cbr /\u003e"]]
