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Results 1 - 10 of 30 for 1x1x2xf32 (0.31 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/tf-tfl-translate-serialize-stablehlo.mlir
module { func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> { %1 = arith.constant dense<1> : tensor<1xi32> %2 = arith.constant dense<2.0> : tensor<1x1x2xf32> %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""} : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32> func.return %3 : tensor<2x1x2xf32> } } //CHECK: module attributes
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 18:33:43 UTC 2024 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tf-tfl-translate-tf-quantize.mlir
module { func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> { %1 = arith.constant dense<1> : tensor<1xi32> %2 = arith.constant dense<2.0> : tensor<1x1x2xf32> %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""} : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32> func.return %3 : tensor<2x1x2xf32> } } //CHECK: module {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 18:33:43 UTC 2024 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%9 = stablehlo.dot_general %8, %2, contracting_dims = [2] x [0] : (tensor<1x4x2xf32>, tensor<2x3xf32>) -> tensor<1x4x3xf32> %10 = stablehlo.convert %3 : (tensor<1x1x3xi32>) -> tensor<1x1x3xf32> %11 = stablehlo.broadcast_in_dim %10, dims = [0, 1, 2] : (tensor<1x1x3xf32>) -> tensor<1x4x3xf32> // Optional %12 = stablehlo.subtract %9, %11 : tensor<1x4x3xf32> // Precalculated zp_neg.
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/lite/tests/optimize.mlir
%1 = "tfl.sqrt"(%0) : (tensor<1x1xf32>) -> tensor<1x1xf32> %2 = "tfl.tile"(%1, %cst_1) : (tensor<1x1xf32>, tensor<2xi32>) -> tensor<1x128xf32> %3 = "tfl.div"(%2, %arg1) {fused_activation_function = "NONE"} : (tensor<1x128xf32>, tensor<1x128xf32>) -> tensor<1x128xf32> func.return %3 : tensor<1x128xf32>
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/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/tf2xla/tests/legalize-tf-BatchMatMulV2.mlir
func.func @batchmatmulv2_basic(%arg0: tensor<1x4x2xf32>, %arg1: tensor<3x2x4xf32>) -> tensor<3x4x4xf32> { // CHECK-LABEL: func @batchmatmulv2_basic // CHECK-SAME: ([[LHS:%.*]]: tensor<1x4x2xf32>, [[RHS:%.*]]: tensor<3x2x4xf32>) -> tensor<3x4x4xf32> // CHECK: [[LHSSHAPE:%.*]] = shape.shape_of [[LHS]] : tensor<1x4x2xf32> // CHECK: [[RHSSHAPE:%.*]] = shape.shape_of [[RHS]] : tensor<3x2x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 5.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver_with_skipping.mlir
%output_0, %min_1, %max_2, %histogram_3 = "tf.CustomAggregator"(%0) <{calibration_method = 1 : i32, id = "keeping_id", max_percentile = 0.000000e+00 : f32, min_percentile = 0.000000e+00 : f32, num_bins = 0 : i32}> : (tensor<10x1x3xf32>) -> (tensor<10x1x3xf32>, tensor<f32>, tensor<f32>, tensor<0xi64>) return %output_0 : tensor<10x1x3xf32> } // CHECK-LABEL: @main
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/post_calibration_component.mlir
} func.func private @composite_dot_general_fn_1(%arg0: tensor<1x1024xf32>, %arg1: tensor<1024x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module} { %0 = stablehlo.dot_general %arg0, %arg1, contracting_dims = [1] x [0] : (tensor<1x1024xf32>, tensor<1024x3xf32>) -> tensor<1x3xf32> return %0 : tensor<1x3xf32> } // CHECK-LABEL: func.func @main // CHECK-SAME: (%[[ARG_0:.+]]: tensor<1x1024xf32>) -> tensor<1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir
time_major = false} : ( tensor<1x2x3xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, none, none, none, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, none, none, tensor<1x3xf32>, tensor<1x3xf32>, none, none, none, none) -> tensor<1x2x3xf32>
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/lite/tests/prepare-quantize-post-training.mlir
// Legacy mode re-calculates zero point when it's changed due to subtle difference in scale. func.func @ZeroPointLegacy(%arg0: tensor<1x2xf32>) -> tensor<1x2xf32> { %0 = "quantfork.stats"(%arg0) {layerStats = dense<[-1.0, 1.20779215]> : tensor<2xf32>} : (tensor<1x2xf32>) -> tensor<1x2xf32> func.return %0 : tensor<1x2xf32> // CHECK: %1 = "tfl.dequantize"(%0) : (tensor<1x2x!quant.uniform<i8:f32, 0.0086580084819419707:-12>>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 52.6K bytes - Viewed (0)