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Results 1 - 10 of 28 for 1x1x1x16xi32 (0.18 sec)
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tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
^bb0(%arg0: tensor<1x7x7x16xf32>): %0 = "tf.AvgPool"(%arg0) {T = "tfdtype$DT_FLOAT", ksize = [1, 7, 7, 1], padding = "VALID", strides = [1, 1, 1, 1]} : (tensor<1x7x7x16xf32>) -> tensor<1x1x1x16xf32> func.return %0 : tensor<1x1x1x16xf32> } // ----- func.func @testAvgPoolWrongDataType(tensor<1x7x7x16xi32>) -> tensor<1x1x1x16xi32> { ^bb0(%arg0: tensor<1x7x7x16xi32>):
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
// Unsupported strides %2 = "tf.MaxPool"(%arg0) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", ksize = [1, 3, 6, 1], padding = "VALID", strides = [1, 3, 1, 3]} : (tensor<1x1x1x16xf32>) -> tensor<1x1x1x16xf32> %5 = arith.addf %0, %1 : tensor<1x1x1x16xf32> %6 = arith.addf %2, %5 : tensor<1x1x1x16xf32> func.return %6 : tensor<1x1x1x16xf32>
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/flatbuffer2mlir/mix_tflite_vhlo.mlir
// test stablehlo roundtrip module { func.func @main(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> { %0 = "vhlo.logistic_v1"(%arg0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> %1 = "tfl.exp"(%0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> loc("exp") func.return %1 : tensor<1x1x1x96xf32> } } // CHECK: func.func @main(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> attributes {tf.entry_function = {inputs = "arg0", outputs = "exp"}} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 907 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops.mlir
return %15 : tensor<1x224x112x512xi8> } // CHECK-LABEL: func @conv_with_filter_larger_than_1MB // CHECK-DAG: %[[CONST:.*]] = "tf.Const"() <{value = dense<-264192> : tensor<1x1x1x512xi32>}> : () -> tensor<1x1x1x512xi32> // CHECK: %[[PADV2_0:.*]] = "tf.PadV2" // CHECK: %[[XLACONVV2_0:.*]] = "tf.XlaConvV2"(%[[PADV2_0]] // CHECK: %[[SUB_0:.*]] = "tf.Sub"(%[[XLACONVV2_0]], %[[CONST]]) } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 81K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/many_attribute_op.mlir
func.func @main(tensor<1x6x6x16xf32>) -> tensor<1x1x1x16xf32> { ^bb0(%arg0: tensor<1x6x6x16xf32>): // CHECK: "tfl.average_pool_2d"(%{{.*}}) <{filter_height = 3 : i32, filter_width = 6 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 3 : i32, stride_w = 1 : i32}> : (tensor<1x6x6x16xf32>) -> tensor<1x1x1x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 824 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir
func.func @exp(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> { %0 = "vhlo.exponential_v1" (%arg0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> func.return %0 : tensor<1x1x1x96xf32> } //CHECK:func.func private @exp(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> { //CHECK-NEXT: %0 = "vhlo.exponential_v1"(%arg0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> //CHECK-NEXT: return %0 : tensor<1x1x1x96xf32> //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 (0) -
tensorflow/compiler/mlir/lite/tests/post-quantize-dynamic-range.mlir
%custom_2 = "tfl.custom"(%arg0, %dq_w) {custom_code = "CustomTestOp", custom_option = #tfl<const_bytes : "0x">} : (tensor<1x1x1x1xf32>, tensor<1024x1x1x1xf32>) -> tensor<*xf32> %custom_3 = "tfl.custom"(%arg0, %dq_w) {custom_code = "CustomTestOp", custom_option = #tfl<const_bytes : "0x">} : (tensor<1x1x1x1xf32>, tensor<1024x1x1x1xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 11.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo_const.mlir
module attributes {tfl.metadata = {"keep_stablehlo_constant" = "true"}} { func.func @main () -> tensor<1x1x1x96xf32> { %0 = "vhlo.constant_v1"() <{value = #vhlo.tensor_v1<dense<0.000000e+00> : tensor<f32>>}> : () -> tensor<1x1x1x96xf32> func.return %0 : tensor<1x1x1x96xf32> } } //CHECK: func.func @main() -> tensor<1x1x1x96xf32> attributes {tf.entry_function = {outputs = "vhlo.constant_v1"}} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 833 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/nn.mlir
func.return %0 : tensor<1x1x1x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 14 16:41:28 UTC 2022 - 2.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/simple-graph.mlir
// CHECK: [[VAL_1:%.*]] = "tfl.reshape"(%2, %[[CST]]) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1xf32>, tensor<4xi32>) -> tensor<1x1x1x1xf32> // CHECK: [[VAL_2:%.*]] = "tfl.concatenation"([[VAL_0]], [[VAL_1]]) <{axis = 3 : i32, fused_activation_function = "NONE"}> {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.6K bytes - Viewed (0)