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Results 11 - 20 of 30 for 1x1x384xf32 (0.14 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions_with_quantization_specs.mlir
// DISABLE-ALL-DOT-GENERAL: @main func.func @main(%arg0: tensor<1x1x167xf32>) -> tensor<1x1x64xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<167x64xf32> %1 = stablehlo.dot_general %arg0, %0, contracting_dims = [2] x [0], precision = [DEFAULT, DEFAULT] : (tensor<1x1x167xf32>, tensor<167x64xf32>) -> tensor<1x1x64xf32> return %1 : tensor<1x1x64xf32> } // DISABLE-ALL-DOT-GENERAL: %[[CONST:.+]] = stablehlo.constant dense<2.000000e+00>
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/lite/tests/flatbuffer2mlir/basic_lstm.mlir
BASIC>, proj_clip = 2.000000e+00 : f32}> {asymmetric_quantize_inputs = false} : (tensor<1x384xf32>, tensor<1x96xf32>, tensor<384x480xf32>, tensor<384xf32>, tensor<1x96xf32>) -> (tensor<1x96xf32>, tensor<1x96xf32>, tensor<1x480xf32>, tensor<1x384xf32>) %0:4 = "tfl.basic_lstm"(%arg0, %arg1, %arg2, %arg3, %arg4) {fused_activation_function = "RELU", cell_clip = 1.0 : f32, proj_clip = 2.0 : f32} : (tensor<1x384xf32>, tensor<1x96xf32>, tensor<384x480xf32>, tensor<384xf32>, tensor<1x96xf32>) -> (tensor<1x96xf32>,...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/fuse_mhlo_convolution.mlir
// CHECK-DAG: %[[CST:.+]] = mhlo.constant dense<[1.000000e-01, 2.000000e-01]> : tensor<2xf32> // CHECK-DAG: %[[CST_BCAST:.+]] = "mhlo.broadcast_in_dim"(%[[CST]]) <{broadcast_dimensions = dense<3> : tensor<1xi64>}> : (tensor<2xf32>) -> tensor<1x1x3x2xf32> // CHECK-DAG: %[[NEW_FILTER:.+]] = mhlo.multiply %[[CST_BCAST]], %[[FILTER]] : tensor<1x1x3x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
} // ----- // CHECK-LABEL: testReverseV2 func.func @testReverseV2(%arg0: tensor<1x2x3x4xf32>, %arg1 : tensor<2xi32>) -> tensor<1x2x3x4xf32> { // CHECK: "tfl.reverse_v2"(%arg0, %arg1) %0 = "tfl.reverse_v2"(%arg0, %arg1): (tensor<1x2x3x4xf32>, tensor<2xi32>) -> tensor<1x2x3x4xf32> func.return %0 : tensor<1x2x3x4xf32> } // ----- // test select // CHECK-LABEL: testSelect
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 189.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/fold_broadcast.mlir
%1 = mhlo.multiply %0, %cst1 : tensor<1x1x2x4xf32> // CHECK: return %[[RES]] : tensor<1x1x2x4xf32> func.return %1 : tensor<1x1x2x4xf32> } // CHECK-LABEL: @foldBroadcastInDimBeforeMulOp_bcast_dim_2D_float func.func @foldBroadcastInDimBeforeMulOp_bcast_dim_2D_float() -> (tensor<1x2x2x3xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_to_nchw.mlir
// RUN: tf-opt %s -tf-layout-optimization=force-data-format=NCHW -verify-diagnostics | FileCheck %s --dump-input=always // CHECK-LABEL: func @transposeConv2D func.func @transposeConv2D(%arg0: tensor<1x3x32x32xf32>, %arg1: tensor<1x1x3x8xf32>) -> tensor<1x8x32x32xf32> { // Convert input: NCHW -> NHWC %0 = "tf.Const"() {value = dense<[0, 2, 3, 1]> : tensor<4xi32>} : () -> tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:47:26 UTC 2022 - 1.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/push-tpose-through-ewise.mlir
%perm = arith.constant dense<[3, 0, 1, 2]> : tensor<4xi32> %0 = "tfl.transpose"(%arg0, %perm) : (tensor<2x3x4x1xf32>, tensor<4xi32>) -> tensor<1x2x3x4xf32> %cst = arith.constant dense<1.0> : tensor<5x2x3x4xf32> %1 = "tfl.add"(%0, %cst) { fused_activation_function = "NONE" } : (tensor<1x2x3x4xf32>, tensor<5x2x3x4xf32>) -> tensor<5x2x3x4xf32> func.return %1 : tensor<5x2x3x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 8.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nhwc.mlir
// dilations, etc...). This test only verifies that changing convolution data // layout will update all the attributes. // CHECK-LABEL: func @transposeConv2D func.func @transposeConv2D(%input: tensor<1x3x32x32xf32>, %filter: tensor<1x1x3x8xf32>) -> tensor<1x8x7x6xf32> { // CHECK: %[[ARG_PERM:.*]] = "tf.Const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi64>}> // CHECK: %[[ARG_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%arg0, %[[ARG_PERM]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
// CHECK: %[[CONV:.+]] = stablehlo.convolution(%[[ARG0]], %[[DQ]]) // CHECK{LITERAL}: dim_numbers = [b, 0, 1, f]x[i, 0, 1, o]->[b, 0, 1, f], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 4 : i64} // CHECK-SAME: (tensor<1x3x3x4xf32>, tensor<1x3x3x4xf32>) -> tensor<1x3x3x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 106.2K 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)