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Results 1 - 10 of 35 for 10x19xf32 (0.2 sec)
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tensorflow/compiler/mlir/tensorflow/tests/compile_mlir_util/constant-folding.mlir
module attributes {tf.versions = {producer = 179 : i32}} { func.func @main(%arg0: tensor<10x19xf32>, %arg1: tensor<19x10xf32> {mhlo.is_same_data_across_replicas = true}) -> tensor<10x19xf32> { %0 = "tf.Shape"(%arg0) : (tensor<10x19xf32>) -> tensor<2xi64> %1 = "tf.Reshape"(%arg1, %0) : (tensor<19x10xf32>, tensor<2xi64>) -> tensor<10x19xf32> func.return %1 : tensor<10x19xf32> } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jul 25 02:54:34 UTC 2023 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_to_hlo_pipeline/sccp-post-shape-inference.mlir
module attributes {tf.versions = {producer = 179 : i32}} { // CHECK-LABEL: func @main func.func @main(%arg0: tensor<10x19xf32>, %arg1: tensor<19x10xf32> {mhlo.is_same_data_across_replicas = true}) -> tensor<?xi64> { %0 = "tf.Shape"(%arg0) : (tensor<10x19xf32>) -> tensor<2xi64> %1 = "tf.Reshape"(%arg1, %0) : (tensor<19x10xf32>, tensor<2xi64>) -> tensor<?x?xf32> // CHECK: %[[RESULT:.*]] = mhlo.constant dense<[10, 19]>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jul 25 02:54:34 UTC 2023 - 1020 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
} func.func @matmul_batchv3_unknown_dim(%arg0: tensor<?x10x15xf32>, %arg1: tensor<15x17xf32>) -> tensor<?x10x17xf32> { %0 = "tf.BatchMatMulV3"(%arg0, %arg1) {Ta = "tfdtype$DT_FLOAT", Tb = "tfdtype$DT_FLOAT", device = "/device:CPU:0", name = "MatMul", adj_x = false, adj_y = false} : (tensor<?x10x15xf32>, tensor<15x17xf32>) -> tensor<?x10x17xf32>
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/tests/prepare-composite-functions-tf.mlir
//...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/convert_tf_quant_to_mhlo_int_test.cc
/*error_tolerance=*/1.0); } TEST_F(ConvertTfQuantToMhloIntTest, UniformQuantizeAddToValidGraph) { constexpr absl::string_view kProgram = R"mlir( func.func @main(%lhs: tensor<10x10xi32>, %rhs: tensor<10x10xi32>) -> tensor<10x10xi32> { %lhs_scale = "tf.Const"() { value = dense<0.518> : tensor<f32> } : () -> tensor<f32> %lhs_zp = "tf.Const"() { value = dense<42> : tensor<i32> } : () -> tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 03 01:03:21 UTC 2024 - 35.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
%1 = "tf.MatMul"(%arg0, %arg0) {device = "", transpose_a = false, transpose_b = false} : (tensor<10x10xi32>, tensor<10x10xi32>) -> tensor<10x10xi32> %2 = "tf.PreventGradient"(%0) : (tensor<10x10xi32>) -> tensor<10x10xi32> %3 = "tf.PreventGradient"(%1) : (tensor<10x10xi32>) -> tensor<10x10xi32> %4 = "tf.AddV2"(%2, %3) {device = ""} : (tensor<10x10xi32>, tensor<10x10xi32>) -> tensor<10x10xi32>
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/tensorflow/tests/tensor_list_ops_decomposition.mlir
// CHECK-SAME: (%[[ARG0:.*]]: tensor<10x8x9xf32>, %[[ARG1:.*]]: tensor<5xi32>, %[[ARG2:.*]]: tensor<5x8x9xf32>) -> tensor<10x8x9xf32> func.func @main(%arg0: tensor<10x8x9xf32>, %arg1: tensor<5xi32>, %arg2: tensor<5x8x9xf32>) -> tensor<10x8x9xf32> { %elem_shape = "tf.Const"() {value = dense<[8, 9]> : tensor<2xi32>} : () -> tensor<2xi32> // CHECK: %[[BUFFER:.*]] = "tf.Identity"(%[[ARG0]]) : (tensor<10x8x9xf32>) -> tensor<10x8x9xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 38.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%0 = arith.constant dense<-1> : tensor<1xi32> %1 = "tfl.reduce_max"(%arg0, %0) {keep_dims = true} : (tensor<10x10xf32>, tensor<1xi32>) -> tensor<10x1xf32> %2 = tfl.sub(%arg0, %1) {fused_activation_function = "NONE"} : (tensor<10x10xf32>, tensor<10x1xf32>) -> tensor<10x10xf32> %3 = "tfl.exp"(%2) : (tensor<10x10xf32>) -> tensor<10x10xf32>
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/tensorflow/tests/graphdef2mlir/mlir_passthrough_op.pbtxt
# CHECK:"tf.MlirPassthroughOp" # CHECK: mlir_module = "\0Afunc @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> {\0A %add = \22tf.Add\22(%arg0, %arg1) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>\0A %ret = \22magic.op\22(%add, %add) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32>\0A return %ret : tensor<10x10xf32>\0A}\0A"}> {device = ""} : (tensor<10xf32>, tensor<10xf32>) -> tensor<*xf32> node { name: "x" op: "Placeholder"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 1.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-dynamic-range-float16.mlir
%2 = "tfl.pseudo_const"() {value = dense<[[0.2]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %3 = "tfl.pseudo_const"() {value = dense<[[0.3]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %4 = "tfl.pseudo_const"() {value = dense<[[0.4]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %5 = "tfl.pseudo_const"() {value = dense<[[0.5]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 4.6K bytes - Viewed (0)