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Results 11 - 16 of 16 for 16x8x8x3xf32 (0.14 sec)
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tensorflow/compiler/mlir/lite/experimental/tac/tests/raise-target-subgraphs.mlir
// CHECK: } // ----- module { func.func @constWeight(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> { %0 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16x3x3x3xf32>} : () -> tensor<16x3x3x3xf32> %1 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16xf32>} : () -> tensor<16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
// CHECK: %0 = "tf.Transpose"(%arg1, %[[CONSTANT0]]) : (tensor<3x3x3x16xf32>, tensor<4xi32>) -> tensor<16x3x3x3xf32> // CHECK: %1 = "tfl.conv_2d"(%arg0, %0, %[[CONSTANT]]) <{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<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32> // CHECK: %2 = "tf.Conv2D"
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/prepare-tf-fake-quant.mlir
func.return %rst : tensor<256x8x7x16xf32> // CHECK-DAG: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<16xf32> // CHECK-DAG: %[[CONSTANT0:.*]] = arith.constant dense<0.000000e+00> : tensor<16x3x3x3xf32> // CHECK: %[[QUANTIZE:.*]] = "tfl.quantize"(%[[CONSTANT0]]) <{qtype = tensor<16x3x3x3x!quant.uniform<u8:f32, 1.000000e+00>>}> // CHECK: %[[DEQUANTIZE:.*]] = "tfl.dequantize"(%[[QUANTIZE]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir
func.return %rst : tensor<256x8x7x16xf32> // CHECK-DAG: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<16xf32> // CHECK-DAG: %[[CONSTANT0:.*]] = arith.constant dense<0.000000e+00> : tensor<16x3x3x3xf32> // CHECK: %[[QUANTIZE:.*]] = "tfl.quantize"(%[[CONSTANT0]]) <{qtype = tensor<16x3x3x3x!quant.uniform<u4:f32, 1.000000e+00>>}> // CHECK: %[[DEQUANTIZE:.*]] = "tfl.dequantize"(%[[QUANTIZE]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
func.return %0 : tensor<256x32x32x16xf32> } // ----- func.func @testConv2D4DBias(tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<1x1x1x16xf32>) -> tensor<256x32x32x16xf32> { ^bb0(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<1x1x1x16xf32>):
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/legalize_hlo.mlir
// CHECK: %[[VAL_8:.*]] = "tf.Transpose"(%[[VAL_6]], %[[VAL_7]]) : (tensor<1x8x8x16xf32>, tensor<4xi64>) -> tensor<16x8x8x1xf32> // CHECK: return %[[VAL_8]] : tensor<16x8x8x1xf32> // CHECK: } func.func @convert_conv2d_with_transpose(%arg0: tensor<8x8x1x207xf32>, %arg1: tensor<3x3x16x207xf32>) -> tensor<16x8x8x1xf32> { %0 = "mhlo.convolution"(%arg0, %arg1) {batch_group_count = 1 : i64, dimension_numbers = #mhlo.conv<raw
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0)