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Results 11 - 20 of 165 for conv_3d (0.21 sec)
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tensorflow/compiler/mlir/lite/tests/optimize_functional_ops.mlir
else_branch = @_functionalize_if_else_branch_00, is_stateless = false, then_branch = @_functionalize_if_then_branch_00} : (tensor<i1>, tensor<i1>, tensor<3x15x14x3xf32>, tensor<3x15x14x3xf32>) -> tensor<i1>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 30 10:34:48 UTC 2022 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_xla_weight_only.mlir
parameters[ {"quantized_ops": ["MatMul"], "internal_func_name": "internal_matmul_fn"}, {"quantized_ops": ["Conv2D"], "internal_func_name": "internal_conv2d_fn"}, {"quantized_ops": ["DepthwiseConv2D"], "internal_func_name": "internal_depthwise_conv2d_fn"}, {"quantized_ops": ["Conv3D"], "internal_func_name": "internal_conv3d_fn"}, {"quantized_ops": ["BatchMatMul"], "internal_func_name": "internal_batch_matmul_fn"} ]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 03 15:43:38 UTC 2023 - 7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel.pbtxt
key: "narrow_range" value { b: true } } attr { key: "num_bits" value { i: 8 } } } node { name: "BoxPredictor_4/ClassPredictor/Conv2D" op: "Conv2D" input: "input" input: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel" attr { key: "T" value { type: DT_FLOAT } } attr {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
// CHECK: %1 = "tfl.conv_2d"(%arg0, %0, %[[CONSTANT]]) <{dilation_h_factor = 2 : i32, dilation_w_factor = 3 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 4 : i32, stride_w = 5 : i32}> : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32> // CHECK: %2 = "tf.Conv2D"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform_patterns.h
PatternRewriter& rewriter) const override; }; // Ensure bias for conv2d op. struct EnsureBiasForConv2d : public OpRewritePattern<TFL::Conv2DOp> { using OpRewritePattern<TFL::Conv2DOp>::OpRewritePattern; LogicalResult matchAndRewrite(TFL::Conv2DOp conv_op, PatternRewriter& rewriter) const override; }; // Pad slice to 4d.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 03 16:37:16 UTC 2022 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq.mlir
func.func @lift_float_conv3d(%arg0: tensor<1x3x4x3x3xf32>) -> (tensor<1x3x2x3x2xf32>) { %cst = "tf.Const"() {device = "", value = dense<1.0> : tensor<2x3x3x3x2xf32>} : () -> tensor<2x3x3x3x2xf32> %0 = "tf.Conv3D"(%arg0, %cst) { data_format = "NDHWC", device = "", dilations = [1, 1, 1, 1, 1], padding = "SAME", strides = [1, 1, 2, 1, 1] } : (tensor<1x3x4x3x3xf32>, tensor<2x3x3x3x2xf32>) -> tensor<1x3x2x3x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/lift_quantizable_spots_as_functions.cc
} else if (function_name.contains("conv2d")) { // For Conv2D, the channel dimension must be static to calculate the // feature group count. if (!HasStaticShapeAtDims(call_op->getOperand(0), /*dims=*/3)) { return absl::InternalError( "The channel dimension of Conv2D is required to be static."); } } else if (function_name.contains("conv3d")) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 16.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel_4bit.pbtxt
key: "narrow_range" value { b: true } } attr { key: "num_bits" value { i: 4 } } } node { name: "BoxPredictor_4/ClassPredictor/Conv2D" op: "Conv2D" input: "input" input: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel" attr { key: "T" value { type: DT_FLOAT } } attr {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
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/quantization/common/quantization_lib/quantization.td
tensor<64x3x3x3xf32> %conv = "tfl.conv_2d"(%input_act, %w, %bias) but if it is supported, it will be rewritten as: %q_w = "tfl.pseudo_qconst"() { qtype = tensor<64x3x3x3x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>> %conv = "tfl.conv_2d"(%input_act, %q_w, %bias) Note that this is part of reaching feature parity with the old quantizer for
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 8.3K bytes - Viewed (0)