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Results 1 - 9 of 9 for 8x16x4xf32 (0.35 sec)
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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/canonicalize.mlir
func.func @reshape_vector_shape(tensor<4x4x4xf32>) -> tensor<16x4xf32> { ^bb0(%arg0: tensor<4x4x4xf32>) : %shape0 = arith.constant dense<[[16, 4]]> : tensor<1x2xi32> // expected-error @+1 {{'tfl.reshape' op requires 'shape' to be rank 1, but got 2}} %1 = "tfl.reshape"(%arg0, %shape0) : (tensor<4x4x4xf32>, tensor<1x2xi32>) -> tensor<16x4xf32> func.return %1 : tensor<16x4xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_default.mlir
func.func @softmax(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.Softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32> func.return %0 : tensor<8x16xf32> // CHECK: %[[CUSTOM_0:.*]] = "tfl.custom"(%arg0) <{custom_code = "FlexSoftmax", custom_option = #tfl<const_bytes : "0x07536F66746D617800161207536F66746D61781A002A070A0154120230013200000221191414042801">}> : (tensor<8x16xf32>) -> tensor<8x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.4K 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) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
%1 = stablehlo.transpose %arg0, dims = [1, 0] : (tensor<16x8xf32>) -> tensor<8x16xf32> %2 = "stablehlo.reduce_window"(%1, %0) ({ ^bb0(%arg1: tensor<f32>, %arg2: tensor<f32>): %3 = stablehlo.maximum %arg1, %arg2 : tensor<f32> stablehlo.return %3 : tensor<f32> }) {window_dimensions = array<i64: 2, 2>, window_strides = array<i64: 2, 2>} : (tensor<8x16xf32>, tensor<f32>) -> tensor<4x8xf32> return %2 : tensor<4x8xf32> }
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/tf2xla/tests/legalize-tf-with-tf2xla-hlo-importer.mlir
func.return %1 : tensor<2xf32> } // CHECK-LABEL: binary_op_broadcast func.func @binary_op_broadcast(%arg0: tensor<4x1xf32>, %arg1: tensor<4x1x4xf32>) -> tensor<4x4x4xf32> { // CHECK: %[[BROADCAST0:.*]] = "mhlo.broadcast_in_dim"(%arg0) <{broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>}> : (tensor<4x1xf32>) -> tensor<4x4x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 38.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// CHECK-NEXT: %[[BMM_0:.*]] = "tfl.batch_matmul"(%[[RESHAPED_0]], %[[RESHAPED_1]]) <{adj_x = false, adj_y = false, asymmetric_quantize_inputs = false}> : (tensor<3x5x12xf32>, tensor<3x12x4xf32>) -> tensor<3x5x4xf32> // CHECK-NEXT: %[[RESHAPED_BMM:.*]] = mhlo.reshape %[[BMM_0]] // CHECK-NEXT: return %[[RESHAPED_BMM]] : tensor<3x5x1x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 40.1K bytes - Viewed (0)