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tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
for dtype in dtype_list: lhs = tf.constant([0, 5, 3, 14], dtype=dtype) rhs = tf.constant([5, 0, 7, 11], dtype=dtype) exp = tf.constant([0, 0, 3, 10], dtype=tf.float32) res = bitwise_ops.bitwise_and(lhs, rhs) tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE ``` }]; let arguments = (ins TF_IntTensor:$x, TF_IntTensor:$y ); let results = (outs
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0) -
RELEASE.md
* Register devices under their legacy names in device_mgr to ease the transition to clusterspec-propagated configurations. * VectorExponential added to distributions. * Add a bitwise module with bitwise_and, bitwise_or, bitwise_xor, and invert functions. * Add fixed-grid ODE integration routines. * Allow passing bounds to ScipyOptimizerInterface.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0)