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Results 1 - 10 of 23 for 1x11x19xf32 (0.28 sec)
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tensorflow/compiler/mlir/tensorflow/tests/einsum.mlir
} func.func @einsum_ellipsis_in_both_sides(%arg0: tensor<1x11x19xf32>, %arg1: tensor<7x11x13x19xf32>) -> tensor<7x11x13xf32> { %0 = "tf.Einsum"(%arg0, %arg1) {device = "", equation = "...IJ,...INJ->...IN"} : (tensor<1x11x19xf32>, tensor<7x11x13x19xf32>) -> tensor<7x11x13xf32> func.return %0 : tensor<7x11x13xf32> // CHECK-LABEL: einsum_ellipsis_in_both_sides
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 25.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%7 = stablehlo.constant dense<5.000000e-01> : tensor<1x1x1xf32> // Output inverse scale (1 / s3). %8 = stablehlo.constant dense<-5> : tensor<1x1x1xi8> // Output zero point (z3). %9 = stablehlo.constant dense<1.250000e+01> : tensor<1x1x1xf32> // Merged scale (s1 * s2). %10 = call @uniform_quantize(%arg0, %1, %2) : (tensor<8x16x16xf32>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<8x16x16xi8> // q1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/optimize.mlir
// CHECK-SAME: }> : (tensor<10x10x10xf32>, tensor<f32>) -> tensor<11x11x11xf32> // CHECK: return %[[RES]] : tensor<11x11x11xf32> } // ----- // CHECK-LABEL: testTwoConsecutivePadsNegativePositiveHighPad func.func @testTwoConsecutivePadsNegativePositiveHighPad(%arg0: tensor<10x10x10xf32>) -> (tensor<11x11x11xf32>) { %0 = mhlo.constant dense<0.000000e+00> : tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 22.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir
//CHECK:func.func private @slice(%arg0: tensor<160x20x1xf32>) -> tensor<1x1x1xf32> { //CHECK-NEXT: %0 = "vhlo.slice_v1"(%arg0) <{limit_indices = #vhlo.tensor_v1<dense<0> : tensor<3xi64>>, start_indices = #vhlo.tensor_v1<dense<1> : tensor<3xi64>>, strides = #vhlo.tensor_v1<dense<1> : tensor<3xi64>>}> : (tensor<160x20x1xf32>) -> tensor<1x1x1xf32> //CHECK-NEXT: return %0 : tensor<1x1x1xf32> //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/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) -
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/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/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/prepare-quantize-dynamic-range.mlir
// MinElement-LABEL: QuantizeCustomOp func.func @QuantizeCustomOp(%arg0: tensor<1x1x1x1xf32>) -> (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>) attributes {tf.entry_function = {inputs = "input", outputs = "custom_op"}} { %0 = "quantfork.stats"(%arg0) {layerStats = dense<[0.000000e+00, 2.550000e+02]> : tensor<2xf32>} : (tensor<1x1x1x1xf32>) -> tensor<1x1x1x1xf32> %w_1 = arith.constant dense<127.0> : tensor<4096x1x1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 38.2K bytes - Viewed (0)