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Results 1 - 10 of 17 for 3x3x1x1xf32 (0.2 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/optimize.mlir
%cst_3 = "tf.Const"() {value = dense<[[[[1.400000e+01]], [[-2.800000e+01]], [[4.200000e+01]]], [[[-5.600000e+01]], [[7.100000e+01]], [[-8.500000e+01]]], [[[9.900000e+01]], [[-1.130000e+02]], [[1.270000e+02]]]]> : tensor<3x3x1x1xf32>} : () -> tensor<3x3x1x1xf32> %cst_4 = "tf.Const"() {value = dense<-1.280000e+02> : tensor<f32>} : () -> tensor<f32> %cst_5 = "tf.Const"() {value = dense<0.00118110236> : tensor<1xf32>} : () -> tensor<1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize-after-quantization.mlir
%cst_0 = arith.constant dense<[1.0, 2.0, 3.0]> : tensor<3xf32> %w = arith.constant dense<2.0> : tensor<3x3x3x3xf32> %q = "tfl.quantize"(%w) {qtype = tensor<3x3x3x3x!quant.uniform<i8:f32, 0.1:1>>} : (tensor<3x3x3x3xf32>) -> tensor<3x3x3x3x!quant.uniform<i8:f32, 0.1:1>> %dq = "tfl.dequantize"(%q) : (tensor<3x3x3x3x!quant.uniform<i8:f32, 0.1:1>>) -> tensor<3x3x3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 1.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/convert_func_to_bfloat16.mlir
stablehlo.return %2 : tensor<f32> }) {padding = dense<[[0, 0], [1, 1], [1, 1], [0, 0]]> : tensor<4x2xi64>, window_dimensions = array<i64: 1, 3, 3, 1>} : (tensor<2x3x1x3xf32>, tensor<f32>) -> tensor<2x3x1x3xf32> return %1 : tensor<2x3x1x3xf32> } // ----- // CHECK-LABEL: @bitcast_convert_i32_f32(%arg0: tensor<1x256128xi32>) -> tensor<1x256128xbf16>
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/quantization/tensorflow/tests/tf_to_quant.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_xla.mlir
%0 = "tf.DepthwiseConv2dNative"(%arg0, %cst_0) {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1]} : (tensor<1x3x4x3xf32>, tensor<2x3x3x1xf32>) -> tensor<1x2x2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_legacy.mlir
// CHECK-LABEL: conv2d_backprop_input_with_add func.func @conv2d_backprop_input_with_add(%arg0: tensor<4xi32>, %arg1: tensor<3x3x1x32xf32>, %arg2: tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32> { %0 = "tf.Conv2DBackpropInput"(%arg0, %arg1, %arg2) {strides = [1, 2, 2, 1], padding="SAME", dilations=[1, 1, 1, 1]}: (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32>
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/experimental/tac/tests/e2e/simple-graph.mlir
// CHECK: [[VAL_1:%.*]] = "tfl.reshape"(%2, %[[CST]]) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1xf32>, tensor<4xi32>) -> tensor<1x1x1x1xf32> // CHECK: [[VAL_2:%.*]] = "tfl.concatenation"([[VAL_0]], [[VAL_1]]) <{axis = 3 : i32, fused_activation_function = "NONE"}> {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-with-allowing-bf16-and-f16-type-legalization.mlir
func.func @depthwise_conv_2d_bf16(%arg0 : tensor<256x32x32x3xbf16>, %arg1 : tensor<3x3x3x4xf32>, %arg2 : tensor<256x3x32x32xf32>) -> tensor<256x30x30x12xbf16> { %0 = "tf.DepthwiseConv2dNative"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xbf16>, tensor<3x3x3x4xf32>) -> tensor<256x30x30x12xbf16> func.return %0 : tensor<256x30x30x12xbf16>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 26 23:53:32 UTC 2022 - 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/lite/tests/push-tpose-through-ewise.mlir
// CHECK: return %1 : tensor<5x2x3x4xf32> // ----- // CHECK-LABEL: pushTposeBcastNoChange func.func @pushTposeBcastNoChange(%arg0: tensor<2x3x4x1xf32>) -> tensor<5x2x3x4xf32> { %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>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 8.9K bytes - Viewed (0)