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Results 1 - 2 of 2 for 2x7x5x4xf32 (0.1 sec)
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tensorflow/compiler/mlir/lite/tests/optimize.mlir
%0 = "tfl.slice"(%arg0, %begin0, %shape0) : (tensor<2x3x4x5xf32>, tensor<4xi64>, tensor<4xi64>) -> tensor<2x3x4x4xf32> %1 = "tfl.slice"(%arg0, %begin1, %shape1) : (tensor<2x3x4x5xf32>, tensor<4xi64>, tensor<4xi64>) -> tensor<1x2x3x4xf32> func.return %0, %1 : tensor<2x3x4x4xf32>, tensor<1x2x3x4xf32> // CHECK-DAG: %[[BEGIN_0:.*]] = arith.constant dense<0> : tensor<4xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// CHECK: }) // CHECK-SAME: -> tensor<2x3x5x7xf32> // CHECK: [[COUNT:%.+]] = mhlo.constant dense<4.000000e+00> : tensor<f32> // CHECK: [[DIV_RESULT:%.+]] = chlo.broadcast_divide [[DIVIDEND]], [[COUNT]] // CHECK-SAME: broadcast_dimensions = array<i64> // CHECK-SAME: -> tensor<2x3x5x7xf32> // CHECK: [[CONV16:%.+]] = mhlo.convert [[DIV_RESULT]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0)