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Results 1 - 10 of 15 for 4x3x6x5xf32 (0.23 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_weight_param.mlir
version = 5 : i64 } : (tensor<4x3x6x5xf32>, tensor<4x3x5x2xf32>) -> tensor<4x3x6x2xf32> return %0 : tensor<4x3x6x2xf32> } // CHECK: func.func private @qdq_for_dot_general_weight_per_channel_default(%[[ARG0:.+]]: tensor<4x3x6x5xf32>) // CHECK: %[[CST:.+]] = "tf.Const"() <{value = dense<3.000000e-01> : tensor<4x3x5x2xf32>}> : () -> tensor<4x3x5x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir
// CHECK: return %[[RESULT]] : tensor<2x3x4x6xf32> } // ----- func.func @batchMatMulTwoDimAdjXY(%arg0: tensor<2x3x5x4xf32>, %arg1: tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32> { %0 = "tf.BatchMatMul"(%arg0, %arg1) {adj_x = true, adj_y = true} : (tensor<2x3x5x4xf32>, tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32> func.return %0 : tensor<2x3x4x6xf32> // CHECK-LABEL: batchMatMulTwoDimAdjXY
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:42:28 UTC 2023 - 63.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/push-tpose-through-ewise.mlir
// CHECK: %0 = tfl.sub %arg0, %cst_0 {fused_activation_function = "NONE"} : tensor<2x3x4x5xf32> // CHECK: %1 = "tfl.transpose"(%0, %cst) : (tensor<2x3x4x5xf32>, tensor<4xi32>) -> tensor<5x2x3x4xf32> // CHECK: return %1 : tensor<5x2x3x4xf32> // ----- // CHECK-LABEL: permNotConstNoChange func.func @permNotConstNoChange(%arg0: tensor<2x3x4x5xf32>, %perm: tensor<4xi32>) -> 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/lite/stablehlo/tests/composite-lowering.mlir
%5 = "mhlo.broadcast_in_dim"(%4) {broadcast_dimensions = dense<[2, 3]> : tensor<2xi64>} : (tensor<6x6xf32>) -> tensor<1x3x6x6xf32> %6 = mhlo.divide %3, %5 : tensor<1x3x6x6xf32> return %6 : tensor<1x3x6x6xf32> } // CHECK-LABEL: func.func @avg_pool2d_2( // CHECK-SAME: %[[VAL_0:.*]]: tensor<1x3x6x6xf32>) -> tensor<*xf32> { // CHECK: %[[VAL_1:.*]] = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/dynamic_shape.mlir
%cst = arith.constant dense<1.0> : tensor<4xf32> %cst_3 = arith.constant dense<2.0> : tensor<4x3x3x3xf32> %0 = "tfl.conv_2d"(%arg0, %cst_3, %cst) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "RELU6", padding = "VALID", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<?x19x19x3xf32>, tensor<4x3x3x3xf32>, tensor<4xf32>) -> tensor<?x9x9x4xf32> func.return %0 : tensor<?x9x9x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 07:35:24 UTC 2022 - 716 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/fold_constant_transpose.mlir
// ----- // CHECK-LABEL: transpose_simple_4d func.func @transpose_simple_4d() -> tensor<5x2x3x4xf32> { %0 = stablehlo.constant dense<1.000000e+0> : tensor<2x3x4x5xf32> %1 = stablehlo.transpose %0, dims = [3, 0, 1, 2] : (tensor<2x3x4x5xf32>) -> tensor<5x2x3x4xf32> return %1 : tensor<5x2x3x4xf32> } // CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant dense<1.000000e+00> : tensor<5x2x3x4xf32> // CHECK-NOT: transpose
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 08:06:02 UTC 2024 - 2.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/order_by_dialect.mlir
%3 = "tf.ReadVariableOp"(%arg2) : (tensor<!tf_type.resource<tensor<5xf32>>>) -> tensor<5xf32> %4 = "tf.ReadVariableOp"(%arg1) : (tensor<!tf_type.resource<tensor<3x3x1x5xf32>>>) -> tensor<3x3x1x5xf32> %5 = "tf.ReadVariableOp"(%arg3) : (tensor<!tf_type.resource<tensor<3920x10xf32>>>) -> tensor<3920x10xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 7.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/strip_tf_attributes.mlir
// CHECK-LABEL: strips_attributes // CHECK-NOT: tf func.func @strips_attributes(%arg0: tensor<32x28x28x1xf32> {tf._user_specified_name = "x"}, %arg1: tensor<3x3x1x5xf32> {tf._user_specified_name = "w1"}, %arg2: tensor<5xf32> {tf._user_specified_name = "b1"}, %arg3: tensor<3920x10xf32> {tf._user_specified_name = "w2"},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 25 20:04:10 UTC 2022 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops.mlir
%6 = "tf.Div"(%arg1, %cst_2) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32> %7 = "tf.AddV2"(%6, %cst_1) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32> %8 = "tf.Maximum"(%7, %cst_1) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32> %9 = "tf.Minimum"(%8, %cst_4) {device = ""} : (tensor<2x3x4x5xf32>, tensor<f32>) -> tensor<2x3x4x5xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 81K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
func.func @ConvertSliceToIdentityI32(%arg0: tensor<2x3x4x5xf32>) -> tensor<2x3x4x5xf32> { %begin = arith.constant dense<0> : tensor<4xi32> %shape = arith.constant dense<[2,3,4,5]> : tensor<4xi32> %0 = "tfl.slice"(%arg0, %begin, %shape) : (tensor<2x3x4x5xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<2x3x4x5xf32> func.return %0 : tensor<2x3x4x5xf32> // CHECK: return %arg0 }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0)