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Results 31 - 40 of 44 for 2x100xf32 (0.24 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_custom_aggregation_ops.mlir
} : (tensor<?x100352xf32>, tensor<100352x10xf32>) -> tensor<?x10xf32> %3 = "tf.Identity"(%2) {device = ""} : (tensor<?x10xf32>) -> tensor<?x10xf32> return %3 : tensor<?x10xf32> } // CHECK-LABEL: func.func private @composite_dot_general_fn_1 func.func private @composite_dot_general_fn_1(%arg0: tensor<?x100352xf32>, %arg1: tensor<100352x10xf32>) -> tensor<?x10xf32> { // CHECK-NOT: tf.CustomAggregator
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 32.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
%166 = "tf.MatMul"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", _output_shapes = ["tfshape$dim { size = 1} dim { size = 1000}"], device = "", name = "matmul", transpose_a = false, transpose_b = false} : (tensor<1x1280xf32>, tensor<1280x1000xf32>) -> tensor<1x1000xf32> func.return %166 : tensor<1x1000xf32> // CHECK-LABEL: matmulNoTransposeAOrB
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/stablehlo/passes/bridge/convert_tf_quant_to_mhlo_int_test.cc
} : (tensor<9x10x!tf_type.qint8>, tensor<f32>, tensor<i32>) -> tensor<9x10xf32> %0 = "tf.MatMul"(%input, %filter_new) { } : (tensor<8x9xf32>, tensor<9x10xf32>) -> tensor<8x10xf32> return %0 : tensor<8x10xf32> })mlir"; constexpr absl::string_view kProgram = R"mlir( func.func @main(%input: tensor<8x9xf32>, %filter: tensor<9x10xi8>) -> tensor<8x10xf32> { %filter_scale = "tf.Const"() { value = dense<0.0235> : tensor<f32> } : ()
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/quantization/tensorflow/tests/cast_bf16_ops_to_f32.mlir
// CHECK: return %[[identity]] : tensor<1x3x2x2xf32> func.func @cast_bf16_matmul_to_fp32(%arg0: tensor<1x10xf32>) -> (tensor<1x2xf32>) { %cst = "tf.Const"() {device = "", value = dense<1.000000e+01> : tensor<10x2xbf16>} : () -> tensor<10x2xbf16> %0 = "tf.Cast"(%arg0) {Truncate = false, device = ""} : (tensor<1x10xf32>) -> tensor<1x10xbf16>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// CHECK-NEXT: return %[[DIV]] : tensor<4x10xf32> %0 = "tf.Softsign"(%arg0) : (tensor<4x10xf32>) -> tensor<4x10xf32> func.return %0 : tensor<4x10xf32> } // ----- // CHECK-LABEL: func @softsign_grad func.func @softsign_grad(%arg0: tensor<4x10xf32>, %arg1: tensor<4x10xf32>) -> tensor<4x10xf32> { // CHECK-NEXT: %[[ONE:.*]] = mhlo.constant dense<1.000000e+00> : tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops.mlir
%12 = "tf.Mul"(%11, %cst) {device = ""} : (tensor<2x1x3xf32>, tensor<f32>) -> tensor<2x1x3xf32> %13 = "tf.Identity"(%12) {device = ""} : (tensor<2x1x3xf32>) -> tensor<2x1x3xf32> %14 = "tf.Identity"(%13) {device = ""} : (tensor<2x1x3xf32>) -> tensor<2x1x3xf32> return %14 : tensor<2x1x3xf32> } // CHECK-LABEL: func @broadcasting_weight_batch_matmul
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 81K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
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/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/lite/experimental/tac/tests/target-annotation.mlir
%2 = "tfl.relu"(%arg0) : (tensor<1xf32>) -> tensor<1xf32> // CHECK: tac.device = "CPU", tac.inference_type = "FLOAT" %3 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32> func.return } func.func @notAnnotateConst(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> { // CHECK-NOT: tac.device tac.inference_type
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 19 19:32:06 UTC 2023 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/group_by_dialect.mlir
%4 = mhlo.constant dense<0.0> : tensor<200x10xf32> %13 = mhlo.constant dense<-0.0> : tensor<f32> %29 = mhlo.reduce(%4 init: %13) applies mhlo.add across dimensions = [1] : (tensor<200x10xf32>, tensor<f32>) -> tensor<200xf32> return } // CHECK: func @handles_mhlo_regions // CHECK: call [[name:@[^(]*]]( // CHECK: func [[name]]() // ----- func.func @handles_regions_that_use_arguments(%arg0: f32, %arg1: 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)