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Results 71 - 80 of 89 for 5x6xf32 (0.52 sec)
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tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_begin.mlir
func.func @move_transpose_handle_broadcast(%arg0:tensor<8x64xf32>, %arg1:tensor<8x64x64xf32>) -> tensor<512x64xf32> { %cst = "tf.Const"() {value = dense<3> : tensor<i32>} : () -> tensor<i32> %cst_1 = "tf.Const"() {value = dense<[2, 0, 1]> : tensor<3xi32>} : () -> tensor<3xi32> %cst_2 = "tf.Const"() {value = dense<[512, 64]> : tensor<2xi32>} : () -> tensor<2xi32> %0 = "tf.ExpandDims"(%arg0, %cst) {device = ""} : (tensor<8x64xf32>, tensor<i32>) -> tensor<8x64x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-prefer-tf2xla.mlir
// NOFALLBACK-LABEL: @xla_svd func.func @xla_svd(%arg0: tensor<1x1xf32>) -> (tensor<1xf32>, tensor<1x1xf32>, tensor<1x1xf32>) { // NOFALLBACK: XlaSvd %s, %u, %v = "tf.XlaSvd"(%arg0) {max_iter = 1, epsilon = 1.0E-09 : f32, precision_config = ""} : (tensor<1x1xf32>) -> (tensor<1xf32>, tensor<1x1xf32>, tensor<1x1xf32>) func.return %s, %u, %v : tensor<1xf32>, tensor<1x1xf32>, tensor<1x1xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 15.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
func.func @add_with_activation_transpose_rank_two(%arg0: tensor<1x2xf32>) -> tensor<2x1xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<2x1xf32> %1 = stablehlo.transpose %arg0, dims = [1, 0] : (tensor<1x2xf32>) -> tensor<2x1xf32> %2 = stablehlo.add %1, %0 : tensor<2x1xf32> return %2 : tensor<2x1xf32> } // CHECK: %[[TRANSPOSE_0:.+]] = stablehlo.transpose
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 14.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/post-quantize.mlir
} func.func @main2(%arg0: tensor<2x4xf32>, %arg1: tensor<2x4xf32>) -> tensor<2x4xf32> { %0 = "tfl.quantize"(%arg0) {qtype = tensor<2x4x!quant.uniform<u8:f32, 0.49803921568627452>>} : (tensor<2x4xf32>) -> tensor<2x4x!quant.uniform<u8:f32, 0.49803921568627452>> %1 = "tfl.quantize"(%arg1) {qtype = tensor<2x4x!quant.uniform<u8:f32, 0.49803921568627452>>} : (tensor<2x4xf32>) -> tensor<2x4x!quant.uniform<u8:f32, 0.49803921568627452>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 19.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/legacy_reshape.json
// CHECK: %0 = "tfl.pseudo_const"() <{value = dense<2> : tensor<2xi32>}> : () -> tensor<2xi32> // CHECK: %1 = "tfl.reshape"(%arg0, %0) : (tensor<1x4xf32>, tensor<2xi32>) -> tensor<2x2xf32> { "version": 3, "operator_codes": [ { "builtin_code": "RESHAPE" } ], "subgraphs": [ { "tensors": [ { "shape": [1, 4],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 986 bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/group_by_dialect.mlir
%one = "glue.constant"() { value = 1: i32 } : () -> i32 %done = "glue.compare" (%one, %one) { predicate = #glue<"compare LTE"> } : (i32, i32) -> i1 %2 = mhlo.constant dense<[[1.1]]> : tensor<1x1xf32> %3 = mhlo.multiply %2, %2 : tensor<1x1xf32> %cst = "tf.Const"() {value = dense<0.0> : tensor<f32>} : () -> tensor<f32> %0 = "tf.AddV2"(%arg0, %cst) {device = "/device:CPU:0"} : (tensor<f32>, tensor<f32>) -> tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 28 23:43:21 UTC 2022 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
func.func @add_dense_dense_float_mixfng_1_n() -> tensor<2x2xf32> { %cst_0 = arith.constant dense<[[1.5, -2.5]]> : tensor<1x2xf32> %cst_1 = arith.constant dense<[[-3.], [4.]]> : tensor<2x1xf32> %0 = "tfl.add"(%cst_0, %cst_1) {fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<2x1xf32>) -> tensor<2x2xf32> func.return %0 : tensor<2x2xf32>
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/tensorflow/tests/graphdef2mlir/tensor-list.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 29 04:41:05 UTC 2021 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
// CHECK-LABEL: func @testLeakyRelu(%arg0: tensor<16xf32>) func.func @testLeakyRelu(tensor<16xf32>) -> tensor<16xf32> { ^bb0(%arg0: tensor<16xf32>): %0 = "tf.LeakyRelu"(%arg0) {alpha = 0.2 : f32} : (tensor<16xf32>) -> tensor<16xf32> func.return %0 : tensor<16xf32> } // ----- func.func @testLeakyWrongAlphaType(tensor<16xf32>) -> tensor<16xf32> { ^bb0(%arg0: 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) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0)