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Results 41 - 46 of 46 for 96xf32 (0.22 sec)
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tensorflow/compiler/mlir/tensorflow/tests/mark_ops_for_outside_compilation.mlir
func.func @tf2xla_fallback_op_approx_top_k(%arg0: tensor<16xf32>) -> (tensor<?xf32>, tensor<?xi32>) { %0:2 = "tf_device.cluster"() ({ // CHECK: tf.ApproxTopK // CHECK-NOT: _xla_outside_compilation %1:2 = "tf.ApproxTopK"(%arg0) {k = 2} : (tensor<16xf32>) -> (tensor<?xf32>, tensor<?xi32>) tf_device.return %1#0, %1#1 : tensor<?xf32>, tensor<?xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 16:22:32 UTC 2024 - 29.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
%0 = "quantfork.stats"(%arg0) { layerStats = dense<[-1.28e-5, 1.27e-5]> : tensor<2xf32> } : (tensor<1x5x5x2xf32>) -> tensor<1x5x5x2xf32> %w = arith.constant dense<[[[[-1.0, 1.0]]], [[[1.0, 2.0]]], [[[-2.0, 1.0]]]]> : tensor<3x1x1x2xf32> %b = arith.constant dense<0.0> : tensor<3xf32> %b2 = arith.constant dense<[1.0e-2, 2.1473647e1, -2.1473647e2]> : tensor<3xf32> %conv = "tfl.conv_2d"(%0, %w, %b) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
// CHECK: return %[[VAL_2]], %[[VAL_3]] : tensor<4xf32>, tensor<4xf32> // CHECK: } func.func @broadcast_atan2(%arg0: tensor<1xf32>, %arg1: tensor<4xf32>) -> (tensor<4xf32>, tensor<4xf32>) { %0 = "mhlo.broadcast_in_dim"(%arg0) <{broadcast_dimensions = dense<[0]> : tensor<1xi64>}> : (tensor<1xf32>) -> tensor<4xf32> %1 = mhlo.atan2 %0, %arg1 : tensor<4xf32> %2 = mhlo.atan2 %arg1, %0 : tensor<4xf32>
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/lite/tests/post-quantize.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 19.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
} else { // Recurse on the subtypes in the variant/resource. Basically if the input // were: // tensor<!tf_type.variant<tensor<?x8xf32>>> // and: // tensor<!tf_type.variant<tensor<10x8xf32>>> // we'll try here to refine tensor<?x8xf32> with tensor<10x8xf32>. auto refined_subtype = mlir::cast<TensorType>( TypeMeet(lhs_element_type_with_subtype.GetSubtypes().front(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
from tensorflow.compiler.mlir.tensorflow.gen_mlir_passthrough_op import mlir_passthrough_op mlir_module = '''python func @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> { %add = "magic.op"(%arg0, %arg1) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32> return %ret : tensor<10x10xf32> } ''' @tf.function def foo(x, y):
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)