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Results 1 - 3 of 3 for 167x64xf32 (0.09 sec)
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tensorflow/compiler/mlir/lite/tests/ops.mlir
%split_dim_2 = arith.constant dense<1> : tensor<1xi32> %4, %5 = "tfl.split"(%split_dim_2, %arg0) {num_splits = 2 : i32} : (tensor<1xi32>, tensor<16x4xf32>) -> (tensor<16x2xf32>, tensor<16x2xf32>) %6:2 = "tfl.split"(%split_dim_2, %arg0) {num_splits = 2 : i32} : (tensor<1xi32>, tensor<16x4xf32>) -> (tensor<16x2xf32>, tensor<16x?xf32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 189.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
// dimensions into a single dimension. For example, // // %shape = arith.constant dense<[1, 128, 64]> : tensor<3xi32> // %reshape = tfl.reshape(%input, %shape) // %input: tensor<128x64xf32> // %fc = tfl.fully_connected(%reshape, %filter, %bias) // {keep_num_dims = false, weights_format = "DEFAULT"} // // can be canonicalized to //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
// ----- // Verify that the batch_dims can be equal to the rank of the indices. func.func @testGatherV2(%arg0: tensor<16x4xf32>, %arg1: tensor<16xi32>) -> tensor<16xf32> { %0 = "tf.Const"() { value = dense<[1]> : tensor<1xi32> } : () -> tensor<1xi32> %1 = "tf.GatherV2"(%arg0, %arg1, %0) {batch_dims = 1 : i64} : (tensor<16x4xf32>, tensor<16xi32>, tensor<1xi32>) -> tensor<16xf32> func.return %1 : tensor<16xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0)