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Results 31 - 40 of 48 for 2x2x1x2xf32 (0.15 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/propagate_quantize_type.mlir
// RUN: tf-quant-opt %s -split-input-file -quant-propagate-quantize-type | FileCheck %s module { func.func @not_propagate_matmul(%arg0: tensor<1x2x2x2xf32>) -> tensor<*xf32> { %cst = "tf.Const"() {value = dense<127> : tensor<2x1024xi8>} : () -> tensor<2x1024xi8> %cst_0 = "tf.Const"() {value = dense<0.0157480314> : tensor<f32>} : () -> tensor<f32> %0 = "tf.Identity"(%cst) : (tensor<2x1024xi8>) -> tensor<2x1024xi8>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/fake_quant_e2e_flow.mlir
func.func @fake_quant_conv(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> { %cst = "tf.Const"() {value = dense<0.000000e+00> : tensor<2xf32>} : () -> tensor<2xf32> %0 = "tf.FakeQuantWithMinMaxArgs"(%arg1) {device = "", max = 2.000000e+00 : f32, min = -1.000000e+00 : f32, narrow_range = false, num_bits = 8 : i64} : (tensor<2x3x3x2xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints_test.cc
module { func.func @main(%arg0: tensor<2x2x2xf32>, %arg1: tensor<2x2x2xf32>) -> tensor<2x2x2xf32> attributes {_from_xla_call_module} { %0 = stablehlo.dot_general %arg0, %arg1, batching_dims = [0] x [0], contracting_dims = [2] x [1], precision = [DEFAULT, DEFAULT] : (tensor<2x2x2xf32>, tensor<2x2x2xf32>) -> tensor<2x2x2xf32> return %0 : tensor<2x2x2xf32> } } )mlir";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 22.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
%w = arith.constant dense<[[[[-1.0, 1.0]]], [[[1.0, 2.0]]], [[[-2.0, 1.0]]]]> : tensor<3x1x1x2xf32> %b = arith.constant dense<[1.0e-2, 2.1473647e1, -2.1473647e2]> : tensor<3xf32> %transpose_conv = "tfl.transpose_conv"(%arg1, %w, %0, %b) { padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32, fused_activation_function = "NONE" } : (tensor<4xi32>, tensor<3x1x1x2xf32>, tensor<1x5x5x2xf32>, tensor<3xf32>) -> tensor<1x5x5x3xf32>
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/quantization/stablehlo/ops/stablehlo_op_quant_spec_test.cc
index_vector_dim = 2>, slice_sizes = array<i64: 1, 2, 2>, indices_are_sorted = false } : (tensor<3x4x2xf32>, tensor<2x3x2xi64>) -> tensor<2x3x2x2xf32> func.return %2 : tensor<2x3x2x2xf32> } } )mlir"; OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleGather); ASSERT_TRUE(module_op); func::FuncOp main_fn = FindMainFuncOp(*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/stablehlo/tests/bridge/optimize.mlir
return %2 : tensor<?x2x2x1xi8> } // ----- // CHECK-LABEL: func @convolution_add_add_f32 func.func @convolution_add_add_f32( %lhs: tensor<?x3x2x1xf32>, %rhs: tensor<2x1x1x1xf32>, %zp_offset: tensor<?x2x2x1xf32>, %bias: tensor<1xf32> ) -> tensor<?x2x2x1xf32> { // CHECK-DAG: %[[conv:.*]] = mhlo.convolution // CHECK-DAG: %[[combined:.*]] = chlo.broadcast_add %[[conv:.*]], %[[zp_offset:.*]]
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/quantization/tensorflow/tests/convert_tpu_model_to_cpu.mlir
// CHECK: %[[cast:.*]] = "tf.Cast"(%[[cst]]) <{Truncate = false}> : (tensor<2x3x3x2xbf16>) -> tensor<2x3x3x2xf32> // CHECK: %[[conv:.*]] = "tf.Conv2D"(%[[ARG0]], %[[cast]]) // CHECK: %[[identity:.*]] = "tf.IdentityN"(%[[conv]]) {device = ""} : (tensor<1x3x2x2xf32>) -> tensor<1x3x2x2xf32> // CHECK: return %[[identity]] : tensor<1x3x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-quant.mlir
} : (tensor<1x6x6x3xf32>, tensor<2x3x3x2x!tf_type.qint8>, tensor<f32>, tensor<i32>) -> tensor<1x4x1x2xf32> func.return %0 : tensor<1x4x1x2xf32> } // ----- // CHECK-LABEL: func @uniform_quantized_convolution_hybrid_same func.func @uniform_quantized_convolution_hybrid_same(%input: tensor<1x2x2x3xf32>) -> tensor<1x2x1x2xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 01:25:29 UTC 2024 - 37.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composit_functions_debugging.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 06 01:23:21 UTC 2023 - 80.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/device-transform-gpu.mlir
// CHECK: %[[VAL_7:.*]] = "tfl.concatenation"(%[[VAL_5]], %[[VAL_6]]) <{axis = 3 : i32, fused_activation_function = "NONE"}> : (tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x2xf32> // CHECK: %[[VAL_8:.*]] = "tfl.reshape"(%[[VAL_7]], %[[VAL_3]]) : (tensor<1x1x1x2xf32>, tensor<1xi32>) -> tensor<2xf32> // CHECK: %[[VAL_9:.*]] = "tfl.reshape"(%[[VAL_8]], %[[VAL_4]]) : (tensor<2xf32>, tensor<2xi32>) -> tensor<2x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 15.6K bytes - Viewed (0)