- Sort Score
- Result 10 results
- Languages All
Results 1 - 10 of 13 for 1x1x8xi32 (0.47 sec)
-
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%11 = stablehlo.convert %3 : (tensor<1x1x3xi32>) -> tensor<1x1x3xf32> %12 = stablehlo.broadcast_in_dim %11, dims = [0, 1, 2] : (tensor<1x1x3xf32>) -> tensor<1x4x3xf32> // Optional %13 = stablehlo.subtract %10, %12 : tensor<1x4x3xf32> // Precalculated zp_neg. %14 = stablehlo.broadcast_in_dim %4, dims = [0, 1, 2] : (tensor<1x1x3xf32>) -> tensor<1x4x3xf32> // Optional
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);
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
// CHECK:} func.func @reshape(%arg0 : tensor<1x128xi32>) -> tensor<4x32x1xi32>{ %0 = "vhlo.reshape_v1"(%arg0) : (tensor<1x128xi32>) -> tensor<4x32x1xi32> func.return %0 : tensor<4x32x1xi32> } //CHECK:func.func private @reshape(%arg0: tensor<1x128xi32>) -> tensor<4x32x1xi32> { //CHECK-NEXT: %0 = "vhlo.reshape_v1"(%arg0) : (tensor<1x128xi32>) -> tensor<4x32x1xi32> //CHECK-NEXT: return %0 : tensor<4x32x1xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 31.9K bytes - Viewed (1) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
func.func @concatConstantTensorsMiddleDim() -> tensor<1x4x3xi32> { %cst_0 = arith.constant dense<0> : tensor<1x2x3xi32> %cst_1 = arith.constant dense<1> : tensor<1x2x3xi32> %0 = "tfl.concatenation"(%cst_0, %cst_1) {axis = 1 : i32, fused_activation_function = "NONE"} : (tensor<1x2x3xi32>, tensor<1x2x3xi32>) -> tensor<1x4x3xi32> func.return %0 : tensor<1x4x3xi32>
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/quantization/stablehlo/tests/bridge/optimize.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 24 02:26:47 UTC 2024 - 10.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir
// CHECK-LABEL: QuantizeReshapeOp func.func @QuantizeReshapeOp(%arg0: tensor<1x1x3xf32>) -> (tensor<1x3xf32>) { %1 = "quantfork.stats"(%arg0) {layerStats = dense<[-1.0, 1.0]> : tensor<2xf32>} : (tensor<1x1x3xf32>) -> tensor<1x1x3xf32> %2 = "tfl.pseudo_const"() {value = dense<[-1, 3]> : tensor<2xi32>} : () -> tensor<2xi32> %3 = "tfl.reshape"(%1, %2) : (tensor<1x1x3xf32>, tensor<2xi32>) -> tensor<1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_sharding_identification.mlir
// Use a four dimension sharding (devices=[1,1,1,1]0) // Since the input tensor only has three dimensions, we expect this to fail. %0 = "tf.XlaSharding"(%arg0) { _XlaSharding = "\08\03\1A\04\01\01\01\01\22\01\00" } : (tensor<1x2x3xi32>) -> tensor<1x2x3xi32> %1 = "tf.A"(%0) : (tensor<1x2x3xi32>) -> (tensor<1x2x3xi32>) func.return %1: tensor<1x2x3xi32> } // ----- // CHECK-LABEL: func @check_retval_sharding_errors
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 20 19:07:52 UTC 2024 - 47.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
%prelu = "tfl.prelu"(%arg0, %cst) : (tensor<1x10x10x3xf32>, tensor<1x1x3xf32>) -> tensor<1x10x10x3xf32> func.return %prelu : tensor<1x10x10x3xf32> // CHECK: %[[cst:.*]] = arith.constant dense<[{{\[}}[1.66394591, 3.61694336, 2.0382936]]]> : tensor<1x1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/shape-inference.mlir
func.func @testReshapeShapeInference(%arg0: tensor<3x4xi32>) -> tensor<*xi32> { %cst = arith.constant dense<[1, 6, 2]> : tensor<3xi32> // CHECK: "tfl.reshape"(%arg0, %cst) : (tensor<3x4xi32>, tensor<3xi32>) -> tensor<1x6x2xi32> %0 = "tfl.reshape"(%arg0, %cst) : (tensor<3x4xi32>, tensor<3xi32>) -> tensor<*xi32> func.return %0 : tensor<*xi32> } } // ----- // CHECK-LABEL: testReshapeShapeInferenceUnknownDim
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 11.5K bytes - Viewed (0)