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Results 11 - 20 of 22 for 2x5x7xf32 (0.26 sec)
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tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
// CHECK: return } func.func @pow(%arg0: tensor<2x1x3xf32>, %arg1: tensor<2x1x1xf32>) -> tensor<2x1x3xf32> { %0 = "tf.Pow"(%arg0, %arg1) : (tensor<2x1x3xf32>, tensor<2x1x1xf32>) -> tensor<2x1x3xf32> func.return %0 : tensor<2x1x3xf32> // CHECK-LABEL: pow // CHECK: %[[pow:.*]] = tfl.pow(%arg0, %arg1) : (tensor<2x1x3xf32>, tensor<2x1x1xf32>) -> tensor<2x1x3xf32> // CHECK: return }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// RUN: odml-to-stablehlo-opt %s -tfl-legalize-hlo -split-input-file | FileCheck %s --dump-input=fail func.func @main(%arg0: tensor<5x7xf32>) -> tensor<5x7xf32> { func.return %arg0: tensor<5x7xf32> // CHECK-LABEL: main // CHECK: return %arg0 : tensor<5x7xf32> } // - transpose // func.func @transpose_2d(%arg0: tensor<2x3xf32>) -> tensor<3x2xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 40.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%cst_add = arith.constant dense<2.0> : tensor<2x512xf32> // Not 1D %cst_weights = arith.constant dense<3.0> : tensor<1024x512xf32> %cst_bias = arith.constant dense<5.0> : tensor<1024xf32> %0 = "tfl.add"(%arg, %cst_add) {fused_activation_function = "NONE"} : (tensor<2x512xf32>, tensor<2x512xf32>) -> tensor<2x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints_test.cc
module { func.func @main(%arg0: tensor<2x2x2xf32>, %arg1: tensor<2x2x2xf32>) -> tensor<2x2x2xf32> attributes {_from_xla_call_module} { %0 = stablehlo.dot_general %arg0, %arg1, batching_dims = [0] x [0], contracting_dims = [2] x [1], precision = [DEFAULT, DEFAULT] : (tensor<2x2x2xf32>, tensor<2x2x2xf32>) -> tensor<2x2x2xf32> return %0 : tensor<2x2x2xf32> } } )mlir";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 22.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
%1 = "tfl.add"(%cst_2, %cst_1) {fused_activation_function = "NONE"} : (tensor<2x2x2xf32>, tensor< 2x2xf32>) -> tensor<2x2x2xf32> %2 = "tfl.add"(%cst_0, %cst_2) {fused_activation_function = "NONE"} : (tensor< 2xf32>, tensor<2x2x2xf32>) -> tensor<2x2x2xf32> func.return %0, %1, %2 : tensor<2x2xf32>, tensor<2x2x2xf32>, tensor<2x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 45.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
func.func @testSelectV2WithWrongBroadcastableArguments(%cond : tensor<3x4xi1>, %arg0 : tensor<2x3x4xf32>, %arg1 : tensor<4x3xf32>) -> tensor<2x3x4xf32> { // expected-error @+1 {{'tfl.select_v2' op operands don't have broadcast-compatible shapes}} %0 = "tfl.select_v2"(%cond, %arg0, %arg1): (tensor<3x4xi1>, tensor<2x3x4xf32>, tensor<4x3xf32>) -> tensor<2x3x4xf32> func.return %0 : tensor<2x3x4xf32> } // ----- // CHECK-LABEL: topk
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/tests/prepare-tf.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_lifting.mlir
func.func @lower_einsum(%arg0: tensor<3x4x5xf32>, %arg1: tensor<3x5x6xf32>) -> tensor<3x4x6xf32> { %0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "ijk,ikm->ijm"}: (tensor<3x4x5xf32>, tensor<3x5x6xf32>) -> tensor<3x4x6xf32> func.return %0 : tensor<3x4x6xf32> } // CHECK-LABEL: lower_einsum // CHECK: "tf.BatchMatMulV2"(%arg0, %arg1) <{adj_x = false, adj_y = false}> : (tensor<3x4x5xf32>, tensor<3x5x6xf32>) -> tensor<3x4x6xf32> // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 03:24:59 UTC 2024 - 33.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize.mlir
func.func @QuantizePad2(tensor<2x1x3x!quant.uniform<u8:f32, 0.1>>, tensor<2x1x3xf32>, tensor<3x2xi32>) -> (tensor<?xf32>, tensor<?xf32>) { ^bb0(%arg0: tensor<2x1x3x!quant.uniform<u8:f32, 0.1>>, %arg1: tensor<2x1x3xf32>, %arg2: tensor<3x2xi32>): %0 = "tfl.dequantize"(%arg0) : (tensor<2x1x3x!quant.uniform<u8:f32, 0.1>>) -> tensor<2x1x3xf32> %1 = "tfl.pad"(%arg1, %arg2) : (tensor<2x1x3xf32>, tensor<3x2xi32>) -> tensor<?xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 67.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// ----- // CHECK-LABEL: matmul_notranspose // CHECK-SAME: (%[[A:.*]]: tensor<5x7xf32>, %[[B:.*]]: tensor<7x11xf32>) func.func @matmul_notranspose(%a: tensor<5x7xf32>, %b: tensor<7x11xf32>) -> tensor<5x11xf32> { // CHECK: "mhlo.dot"(%[[A]], %[[B]]) %0 = "tf.MatMul"(%a, %b) {transpose_a = false, transpose_b = false} : (tensor<5x7xf32>, tensor<7x11xf32>) -> tensor<5x11xf32> func.return %0 : tensor<5x11xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0)