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Results 1 - 3 of 3 for MaxPool (0.14 sec)
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tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// ----- // CHECK-LABEL: maxpool_explicit_padding func.func @maxpool_explicit_padding(%arg0: tensor<2x12x20x7xi32>) -> tensor<2x3x5x7xi32> { // CHECK: tf.MaxPool // TODO(b/165938852): need to support explicit padding in max_pool. %0 = "tf.MaxPool"(%arg0) {data_format = "NHWC", ksize = [1, 2, 2, 1], padding = "EXPLICIT", strides = [1, 4, 4, 1]} : (tensor<2x12x20x7xi32>) -> tensor<2x3x5x7xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
} // CHECK-LABEL: func @convert_maxpool_valid( // CHECK-SAME: %[[VAL_0:.*]]: tensor<4x16x16x8xf32>) -> tensor<4x7x7x8xf32> { // CHECK: %[[VAL_1:.*]] = "tf.MaxPool"(%[[VAL_0]]) <{data_format = "NHWC", explicit_paddings = [], ksize = [1, 3, 3, 1], padding = "VALID", strides = [1, 2, 2, 1]}> : (tensor<4x16x16x8xf32>) -> tensor<4x7x7x8xf32> // CHECK: return %[[VAL_1]] : tensor<4x7x7x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
}; using ConvertAvgPool2DGradOp = ConvertAvgPoolGradOp<TF::AvgPoolGradOp, /*num_dims=*/4>; using ConvertAvgPool3DGradOp = ConvertAvgPoolGradOp<TF::AvgPool3DGradOp, /*num_dims=*/5>; // Converts MaxPool op to HLO ReduceWindow op by setting appropriate window // dimensions with max as the reduction function. // // Sample result for VALID padding mode: // // %init = arith.constant dense<...> : tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0)