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Results 1 - 10 of 25 for 2x2xf64 (0.21 sec)
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tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-with-tf2xla-hlo-importer.mlir
func.func @xla_spmd_full_to_shard_shape(%arg0: tensor<2x2xi64>) -> (tensor<1x2xi64>) { // CHECK: %[[SHARDING:.*]] = mhlo.custom_call @Sharding(%arg0) {backend_config = "", mhlo.sharding = "{devices=[2,1]0,1}"} : (tensor<2x2xi64>) -> tensor<2x2xi64> // CHECK: %[[MANUAL:.*]] = mhlo.custom_call @SPMDFullToShardShape(%[[SHARDING]]) {backend_config = "", mhlo.sharding = "{manual}"} : (tensor<2x2xi64>) -> tensor<1x2xi64> // CHECK: return %[[MANUAL]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 38.6K bytes - Viewed (1) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-collective.mlir
%group_assignment = "tf.Const"() { value = dense<[[0],[1]]> : tensor<2x1xi32> } : () -> tensor<2x1xi32> // CHECK: "mhlo.all_reduce" // CHECK{LITERAL}: replica_groups = dense<[[0], [1]]> : tensor<2x1xi64> // CHECK-NOT: channel_handle // CHECK: mhlo.add %0 = "tf.XlaAllReduce"(%input, %group_assignment) {reduce_op = "Add", mode = "CrossReplica"} : (tensor<f32>, tensor<2x1xi32>) -> tensor<f32> func.return %0 : tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 15.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize/quantize_op_with_region.mlir
// CHECK: %[[REDUCE:.*]] = "stablehlo.reduce_window"(%[[CALL]], %[[Q0]]) // CHECK{LITERAL}: padding = dense<[[0, 0], [1, 1], [1, 1], [0, 0]]> : tensor<4x2xi64> // CHECK-SAME: window_dimensions = array<i64: 1, 3, 3, 1> // CHECK: %[[ARG1:.*]]: tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>, %[[ARG2:.*]]: tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 18.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir
//CHECK-NEXT: return %0 : tensor<1x161x1xf32> //CHECK-NEXT:} func.func @convert(%arg0: tensor<2xf64>) -> tensor<2xf32> { %0 = "vhlo.convert_v1" (%arg0) : (tensor<2xf64>) -> tensor<2xf32> return %0 : tensor<2xf32> } //CHECK:func.func private @convert(%arg0: tensor<2xf64>) -> tensor<2xf32> { //CHECK-NEXT: %0 = "vhlo.convert_v1"(%arg0) : (tensor<2xf64>) -> tensor<2xf32> //CHECK-NEXT: return %0 : tensor<2xf32> //CHECK-NEXT:}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 31.9K bytes - Viewed (1) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_sharding_identification.mlir
%1 = "tf.Identity"(%0) : (tensor<2x2xf32>) -> tensor<2x2xf32> return %1 : tensor<2x2xf32> } // ----- // The following op sharding is used in the following test case: // Proto debug string: // type: MAXIMAL // tile_assignment_dimensions: 1 // tile_assignment_devices: 0 // Serialized string: // "\08\01\1A\01\01\22\01\00" // Proto debug string: // type: MAXIMAL
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 20 19:07:52 UTC 2024 - 47.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/add_dump_tensor_op.mlir
return %0 : tensor<2x2xf32> } func.func private @composite_matmul_fn_1(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_b", device = "", transpose_a = false, transpose_b = false} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32> return %0 : tensor<2x2xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 37.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints_test.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 22.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
%0 = "tf.Div"(%arg0, %cst) : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32> func.return %0 : tensor<2x2xf32> // CHECK-LABEL: RemoveTrivialDiv // CHECK-NEXT: return %arg0 : tensor<2x2xf32> } func.func @RemoveTrivialRealDiv(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> { %cst = arith.constant dense<1.0> : tensor<2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 31 23:22:24 UTC 2024 - 36.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
} // CHECK-LABEL: prepareAdd func.func @prepareAdd(%arg0: tensor<2x2xf32>) -> tensor<2x2xf32> { %cst = arith.constant dense<[[0.0, 1.0], [2.0, 255.0]]> : tensor<2x2xf32> %add = "tfl.add"(%arg0, %cst) {fused_activation_function="NONE"} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32> func.return %add : tensor<2x2xf32>
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/quantization/tensorflow/tests/add_dump_tensor_op_stablehlo.mlir
%2 = "tf.XlaCallModule"(%arg0, %1, %0) <{Sout = [#tf_type.shape<?x2>], module = "", version = 9 : i64}> {_entry_function = @composite_dot_general_with_bias_and_relu6_dynamic_fn_2, _original_entry_function = "composite_dot_general_with_bias_and_relu6_dynamic_fn_2", _tfl_quant_trait = "fully_quantizable"} : (tensor<?x2xf32>, tensor<2x2xf32>, tensor<2xf32>) -> tensor<?x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 18K bytes - Viewed (0)