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Results 1 - 5 of 5 for 16x16x4xf32 (0.17 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
// input shape. // CHECK-LABEL: reduce_window_max_activation_transpose func.func @reduce_window_max_activation_transpose(%arg0: tensor<1x16x16x4xf32>) -> tensor<1x4x8x8xf32> { %0 = stablehlo.constant dense<0xFF800000> : tensor<f32> // -inf %1 = stablehlo.transpose %arg0, dims = [0, 3, 1, 2] : (tensor<1x16x16x4xf32>) -> tensor<1x4x16x16xf32> %2 = "stablehlo.reduce_window"(%1, %0) ({ ^bb0(%arg1: tensor<f32>, %arg2: tensor<f32>):
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/stablehlo/tests/compose-uniform-quantized-type.mlir
%19 = stablehlo.convert %18 : (tensor<8x16x4xi32>) -> tensor<8x16x4xf32> %20 = stablehlo.broadcast_in_dim %9, dims = [0, 1, 2] : (tensor<1x1x1xf32>) -> tensor<8x16x4xf32> %21 = stablehlo.multiply %19, %20 : tensor<8x16x4xf32> // * s1 s2 %22 = call @uniform_quantize_1(%21, %7, %8) : (tensor<8x16x4xf32>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<8x16x4xi8>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/ops/stablehlo_op_quant_spec_test.cc
return %0 : tensor<1x1x4xf32> } )mlir"; OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleXlaCallModuleOpWithDefaultQuantizationMethod); ASSERT_TRUE(module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 04 07:19:09 UTC 2024 - 14.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc
return %0 : tensor<1x1x4xf32> } )mlir"; const OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kXlaCallModuleOpWithQuantizationMethodAttr); ASSERT_TRUE(module_op); func::FuncOp main_fn = FindMainFuncOp(*module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir
precision_config = #vhlo.array_v1<[#vhlo<precision_v1 DEFAULT>, #vhlo<precision_v1 DEFAULT>]>}> : (tensor<1x1x167xf32>, tensor<167x64xf32>) -> tensor<1x1x64xf32> return %0 : tensor<1x1x64xf32> } //CHECK:func.func private @dot_general(%arg0: tensor<1x1x167xf32>, %arg1: tensor<167x64xf32>) -> tensor<1x1x64xf32> { //CHECK-NEXT: %0 = "vhlo.dot_general_v1"(%arg0, %arg1) <{ //CHECK-SAME: lhs_batching_dimensions = #vhlo.tensor_v1<dense<0> : tensor<1xi64>>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 31.9K bytes - Viewed (0)