From 1a4bf629601dd24a545ab4e9f2e1b4fd746400df Mon Sep 17 00:00:00 2001
From: NAUD Maxence <maxence.naud@cea.fr>
Date: Thu, 24 Oct 2024 12:25:21 +0000
Subject: [PATCH] Remove merge artifacts
---
aidge_export_cpp/operators.py | 173 ----------------------------------
1 file changed, 173 deletions(-)
diff --git a/aidge_export_cpp/operators.py b/aidge_export_cpp/operators.py
index 4943081..9654a20 100644
--- a/aidge_export_cpp/operators.py
+++ b/aidge_export_cpp/operators.py
@@ -192,7 +192,6 @@ class MaxPoolCPP(ExportNodeCpp):
# No padding with MaxPooling
# Use PaddedMaxPooling to add padding attribute
-<<<<<<< HEAD
self.attributes["padding"] = [0, 0]
self.attributes["pool_type"] = "Max"
self.attributes["activation"] = "Linear"
@@ -281,175 +280,3 @@ class FcCPP(ExportNodeCpp):
str(ROOT / "kernels" / "activation.hpp"),
str(ROOT / "kernels" / "rescaling.hpp")
]
-=======
- self.padding = [0, 0]
-
- if len(self.inputs_dims[0]) == 4:
- # if dims == [batch, nb_channels, height, width]
- # transform to [nb_channels, height, width]
- self.inputs_dims[0] = self.inputs_dims[0][1:]
-
- if len(self.outputs_dims[0]) == 4:
- # if dims == [batch, nb_outputs]
- # transform to [nb_outputs, 1, 1]
- self.outputs_dims[0] = self.outputs_dims[0][1:]
-
- def export(self, export_folder:Path, list_configs:list):
-
- copyfile(str(ROOT / "kernels" / "pooling.hpp"),
- str(export_folder / "include" / "kernels"))
-
- list_configs.append("kernels/pooling.hpp")
- list_configs.append(f"layers/{self.name}.h")
-
- generate_file(
- str(export_folder / "layers" / f"{self.name}.h"),
- str(ROOT / "templates" / "configuration" / "pooling_config.jinja"),
- name=self.name,
- input_dims=self.inputs_dims[0],
- output_dims=self.outputs_dims[0],
- kernel=self.kernel,
- stride=self.stride,
- padding=self.padding,
- pool_type="Max",
- activation="Linear")
-
- return list_configs
-
- def forward(self, list_actions:list):
-
- if not self.is_last:
- list_actions.append(set_up_output(self.name, "float"))
-
- list_actions.append(generate_str(
- str(ROOT / "templates" / "kernel_forward" / "pooling_forward.jinja"),
- name=self.name,
- input_name=self.inputs[0].name() if self.inputs[0] else self.name + "_input",
- output_name=self.name
- ))
- return list_actions
-
-@operator_register("FC")
-class FcCPP(ExportNode):
- def __init__(self, node):
- super().__init__(node)
-
- if len(self.inputs_dims[0]) == 4:
- # if dims == [batch, nb_channels, height, width]
- # transform to [nb_channels, height, width]
- self.inputs_dims[0] = self.inputs_dims[0][1:]
- elif len(self.inputs_dims[0]) == 2:
- # if dims == [batch, nb_channels]
- # transform to [nb_channels, 1, 1]
- self.inputs_dims[0] = [self.inputs_dims[0][1], 1, 1]
-
- if len(self.outputs_dims[0]) == 2:
- # if dims == [batch, nb_outputs]
- # transform to [nb_outputs, 1, 1]
- self.outputs_dims[0] = [self.outputs_dims[0][1], 1, 1]
-
-
- def export(self, export_folder:Path, list_configs:list):
-
- copyfile(str(ROOT / "kernels" / "fullyconnected.hpp"),
- str(export_folder / "include" / "kernels"))
- copyfile(str(ROOT / "kernels" / "macs.hpp"),
- str(export_folder / "include" / "kernels"))
- copyfile(str(ROOT / "kernels" / "activation.hpp"),
- str(export_folder / "include" / "kernels"))
-
- # Add to config list the include of configurations
- list_configs.append("kernels/fullyconnected.hpp")
- list_configs.append(f"layers/{self.name}.h")
-
- # Export configuration file
- generate_file(
- str(export_folder / "layers" / f"{self.name}.h"),
- str(ROOT / "templates" / "configuration" / "fullyconnected_config.jinja"),
- name=self.name,
- input_dims=self.inputs_dims[0],
- output_dims=self.outputs_dims[0],
- activation="Linear",
- rescaling="NoScaling")
-
- return list_configs
-
- def forward(self, list_actions:list):
- if not self.is_last:
- list_actions.append(set_up_output(self.name, "float"))
- list_actions.append(generate_str(
- str(ROOT / "templates" / "kernel_forward" / "fullyconnected_forward.jinja"),
- name=self.name,
- inputs_name= self.inputs[0].name() if (self.inputs[0] is not None) else self.name + '_input',
- weights_name=self.inputs[1].name(),
- biases_name=self.inputs[2].name(),
- outputs_name=self.name
- ))
- return list_actions
-
-@operator_register("MatMul")
-class MatMulCPP(ExportNode):
- def __init__(self, node):
- super().__init__(node)
-
- dims0, dims1, outdims = [tuple(x) for x in [self.inputs_dims[0], self.inputs_dims[1], self.outputs_dims[0]]]
-
- # TODO: MatMul aidge operator supports N-D multi broadcast dimensions where N > 2
- assert len(dims0) <= 2 and len(dims1) <= 2, (
- f"MatMul export do not support yet dimensions above 2D: inputs shapes are: {dims0}, {dims1}")
-
- # Cast to at least 1D
- # Note that from MatMul::forwardDims(), scalar inputs are supported
- # which is actually more general than np.matmul
- dims0 = dims0 if len(dims0) >= 1 else (1, 1)
- dims1 = dims1 if len(dims1) >= 1 else (1, 1)
-
- # Cast to at least 2D
- dims0 = dims0 if len(dims0) >= 2 else (1, dims0[0])
- dims1 = dims1 if len(dims1) >= 2 else (dims1[0], 1)
- assert dims0[1] == dims1[0], (
- f"MatMul input dimensions do no match, expected (m, k), (k, n): inputs shapes are: {dims0}, {dims1}")
-
- outdims = outdims if len(outdims) > 0 else (1, 1)
- assert outdims == (dims0[0], dims1[1]), (
- f"MatMul output dimensions do no match, expected (m, n) for inputs (m, k) (k, n): output shape is: {outdims}, inputs shapes are: {dims0}, {dims1}")
-
- self.matmul_inputs_dims = dims0, dims1
- self.matmul_output_dims = outdims
-
- def export(self, export_folder:Path, list_configs:list):
-
- copyfile(str(ROOT / "kernels" / "matmul.hpp"),
- str(export_folder / "include" / "kernels"))
- copyfile(str(ROOT / "kernels" / "activation.hpp"),
- str(export_folder / "include" / "kernels"))
-
- # Add to config list the include of configurations
- list_configs.append("kernels/matmul.hpp")
- list_configs.append(f"layers/{self.name}.h")
-
- # Export configuration file
- generate_file(
- str(export_folder / "layers" / f"{self.name}.h"),
- str(ROOT / "templates" / "configuration" / "matmul_config.jinja"),
- name=self.name,
- inputs_dims=self.matmul_inputs_dims,
- output_dims=self.matmul_output_dims,
- activation="Linear",
- rescaling="NoScaling",
- )
-
- return list_configs
-
- def forward(self, list_actions:list):
- if not self.is_last:
- list_actions.append(set_up_output(self.name, "float"))
- list_actions.append(generate_str(
- str(ROOT / "templates" / "kernel_forward" / "matmul_forward.jinja"),
- name=self.name,
- inputs1_name=self.inputs[0].name() if self.inputs[0] else self.name + "_input1",
- inputs2_name=self.inputs[1].name() if self.inputs[1] else self.name + "_input2",
- outputs_name=self.name
- ))
- return list_actions
->>>>>>> origin/dev
--
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