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tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions_with_quantization_specs.mlir
// RUN: -split-input-file | FileCheck %s --check-prefix=STATIC-RANGE-PTQ-TO-COMPUTE-HEAVY // STATIC-RANGE-PTQ-TO-COMPUTE-HEAVY: @main func.func @main(%arg0: tensor<1x2xf32>) -> tensor<1x2xf32> { %0 = stablehlo.add %arg0, %arg0 : tensor<1x2xf32> return %0 : tensor<1x2xf32> } // Tests that `composite_add_fn_1` does not quantize when quantizing // only compute-heavy ops.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 02 18:09:38 UTC 2024 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
// deferred. // CHECK-LABEL: add_with_activation_transpose_rank_two func.func @add_with_activation_transpose_rank_two(%arg0: tensor<1x2xf32>) -> tensor<2x1xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<2x1xf32> %1 = stablehlo.transpose %arg0, dims = [1, 0] : (tensor<1x2xf32>) -> tensor<2x1xf32> %2 = stablehlo.add %1, %0 : tensor<2x1xf32> return %2 : tensor<2x1xf32> }
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/quantization/stablehlo/tests/passes/convert_func_to_bfloat16.mlir
return %0 : tensor<3x3xf64> } // ----- // CHECK-LABEL: @constant_f32() -> tensor<2x2xbf16> func.func @constant_f32() -> tensor<2x2xf32> { // CHECK-NOT: f32 // CHECK{LITERAL}: stablehlo.constant dense<[[1.398440e+00, 0.000000e+00], [3.093750e+00, -2.001950e-01]]> : tensor<2x2xbf16> %0 = stablehlo.constant dense<[[1.4, 0.0], [3.1, -0.2]]> : tensor<2x2xf32> return %0 : tensor<2x2xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 08 22:40:14 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize_no_verify.mlir
%0 = "tfl.conv_2d"(%arg0, %arg1, %cst_0) {dilation_h_factor = 2 : i32, dilation_w_factor = 3 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 4 : i32, stride_w = 5 : i32} : (tensor<256x32x32x3xf16>, tensor<16x3x3x3xf16>, tensor<16xf16>) -> tensor<256x8x7x16xf16>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize.mlir
} // CHECK-LABEL: QuantizeConcat func.func @QuantizeConcat(tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<2x2x!quant.uniform<u8:f32, 1.000000e-01:128>> { ^bb0(%arg0: tensor<1x2xf32>, %arg1: tensor<1x2xf32>): %0 = "tfl.concatenation"(%arg0, %arg1) {axis = 0 : i32, fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 39.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_sharding_identification.mlir
%0 = "tf_device.cluster_func"(%arg0, %arg1) {func = @_func, use_spmd_for_xla_partitioning = true, use_tpu = true, num_cores_per_replica = 2 : i64} : (tensor<2x4xf32>, tensor<4x2xf32>) -> tensor<2x2xf32> %1:2 = "tf.TPUPartitionedOutputV2"(%0) {device = "", partition_dims = [2, 1]} : (tensor<2x2xf32>) -> (tensor<1x2xf32>, tensor<1x2xf32>)
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-tf.mlir
} func.func @QDQsFollowedByTranspose(tensor<1x2xf32>) -> (tensor<2x1xf32>) { ^bb0(%arg0: tensor<1x2xf32>): %cst_0 = arith.constant dense<[1, 0]> : tensor<2xi32> %0 = "tfl.quantize"(%arg0){qtype = tensor<1x2x!quant.uniform<u8:f32, 1.0>>}: (tensor<1x2xf32>) -> (tensor<1x2x!quant.uniform<u8:f32, 1.0>>) %1 = "tfl.dequantize"(%0): (tensor<1x2x!quant.uniform<u8:f32, 1.0>>) -> (tensor<1x2xf32>)
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/lite/tests/const-fold.mlir
func.func @add_dense_dense_float_mixfng_1_n() -> tensor<2x2xf32> { %cst_0 = arith.constant dense<[[1.5, -2.5]]> : tensor<1x2xf32> %cst_1 = arith.constant dense<[[-3.], [4.]]> : tensor<2x1xf32> %0 = "tfl.add"(%cst_0, %cst_1) {fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<2x1xf32>) -> tensor<2x2xf32> func.return %0 : tensor<2x2xf32>
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/tfr/tests/canonicalize.mlir
// Tests for ops with canonicalization patterns. // CHECK-LABEL: get_real_shape func.func @get_real_shape(%arg0: tensor<1x2xf32>) -> tensor<2xindex> { %0 = "tfr.cast"(%arg0) : (tensor<1x2xf32>) -> !tfr.tensor %1 = tfr.get_shape %0 -> !shape.shape %2 = shape.to_extent_tensor %1 : !shape.shape -> tensor<2xindex> func.return %2 : tensor<2xindex>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints_test.cc
)mlir"; constexpr absl::string_view kModuleHybridQuantized = R"mlir( module { func.func @main(%arg0: tensor<1x2xf32>, %arg1: tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03:0>> {tf_saved_model.index_path = ["input_tensor"]}) -> (tensor<1x3xf32>) { %0 = stablehlo.dot_general %arg0, %arg1, contracting_dims = [1] x [0] : (tensor<1x2xf32>, tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03:0>>) -> tensor<1x3xf32> return %0 : tensor<1x3xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 22.9K bytes - Viewed (0)