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Results 1 - 10 of 34 for 16x28xf32 (0.25 sec)
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tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
func.return %8#2 : tensor<28x1x8xf32>...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training.mlir
: ( tensor<1x28x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x20xf32>, tensor<20x20xf32>, tensor<20x20xf32>, tensor<20x20xf32>, none, none, none, tensor<20xf32>, tensor<20xf32>, tensor<20xf32>, tensor<20xf32>, none, none, tensor<1x20xf32>, tensor<1x20xf32>, none, none, none, none) -> tensor<1x28x20xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 52.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
func.func @reshape_vector_shape(tensor<4x4x4xf32>) -> tensor<16x4xf32> { ^bb0(%arg0: tensor<4x4x4xf32>) : %shape0 = arith.constant dense<[[16, 4]]> : tensor<1x2xi32> // expected-error @+1 {{'tfl.reshape' op requires 'shape' to be rank 1, but got 2}} %1 = "tfl.reshape"(%arg0, %shape0) : (tensor<4x4x4xf32>, tensor<1x2xi32>) -> tensor<16x4xf32> func.return %1 : tensor<16x4xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%0 = "tfl.fully_connected" (%arg0, %arg1, %arg2) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x256xf32>, tensor<128x256xf32>, tensor<128xf32>) -> tensor<1x128xf32> %1 = "tfl.relu"(%0) : (tensor<1x128xf32>) -> tensor<1x128xf32> func.return %1 : tensor<1x128xf32>
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/lite/tests/optimize_batch_matmul.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
// CHECK: [[VAL_12:%.*]]:4 = "tf.SplitV"([[VAL_7]], [[VAL_10]], [[VAL_11]]) : (tensor<40x8xf32>, tensor<4xi32>, tensor<i32>) -> (tensor<10x8xf32>, tensor<10x8xf32>, tensor<10x8xf32>, tensor<10x8xf32>) // CHECK-DAG: [[VAL_13:%.*]] = "tf.Const"() <{value = dense<10> : tensor<4xi32>}> : () -> tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
// CHECK-SAME: -> tensor<!tf_type.variant<tensor<16x1xf32>>> func.func @while_variant(%arg0: tensor<!tf_type.variant<tensor<16x1xf32>>>) -> tensor<!tf_type.variant> { // CHECK: tf.While // CHECK-SAME: -> tensor<!tf_type.variant<tensor<16x1xf32>>> %0 = "tf.While"(%arg0) {cond = @variant_cond_func, body = @variant_body_func, is_stateless = true} : (tensor<!tf_type.variant<tensor<16x1xf32>>>) -> tensor<!tf_type.variant>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
%split_dim_2 = arith.constant dense<1> : tensor<1xi32> %4, %5 = "tfl.split"(%split_dim_2, %arg0) {num_splits = 2 : i32} : (tensor<1xi32>, tensor<16x4xf32>) -> (tensor<16x2xf32>, tensor<16x2xf32>) %6:2 = "tfl.split"(%split_dim_2, %arg0) {num_splits = 2 : i32} : (tensor<1xi32>, tensor<16x4xf32>) -> (tensor<16x2xf32>, tensor<16x?xf32>)
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/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir
%1 = "tf.PartitionedCall"(%arg0, %cst_0) {_tfl_quant_trait = "fully_quantizable", config = "", config_proto = "", executor_type = "", f = @composite_matmul_fn_1} : (tensor<2x12xf32>, tensor<12x2xf32>) -> tensor<*xf32> func.return %1: tensor<*xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/cc/saved_model_import_test.cc
// MLIR @main function corresponds to the TF function "main_original". OwningOpRef<ModuleOp> module_op = ParseModuleOpString(R"mlir( func.func private @main(%arg: tensor<1x2xf32>) -> (tensor<1x2xf32>) attributes {tf._original_func_name = "main_original"} { return %arg : tensor<1x2xf32> } )mlir"); ASSERT_TRUE(module_op); absl::flat_hash_map<FunctionName, FunctionAlias> function_aliases;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 07 03:47:17 UTC 2024 - 4.6K bytes - Viewed (0)