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Commit f7915ed7 authored by auphelia's avatar auphelia
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[fpgadataflow] Newly formatted files

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src/finn/custom_op/fpgadataflow/__init__.py
+ 7
− 8
View file @ f7915ed7
...@@ -6,7 +6,7 @@ class HLSCustomOp(CustomOp): ...@@ -6,7 +6,7 @@ class HLSCustomOp(CustomOp):
def __init__(self): def __init__(self):
super().__init__() super().__init__()
# template for single node execution # template for single node execution
self.docompute_template= """ self.docompute_template = """
#include "cnpy.h" #include "cnpy.h"
#include <vector> #include <vector>
#include "bnn-library.h" #include "bnn-library.h"
...@@ -20,19 +20,19 @@ class HLSCustomOp(CustomOp): ...@@ -20,19 +20,19 @@ class HLSCustomOp(CustomOp):
int main(){ int main(){
$STREAMDECLARATIONS$ $STREAMDECLARATIONS$
$READNPYDATA$ $READNPYDATA$
$DOCOMPUTE$ $DOCOMPUTE$
$DATAOUTSTREAM$ $DATAOUTSTREAM$
$SAVEASCNPY$ $SAVEASCNPY$
} }
""" """
@abstractmethod @abstractmethod
def get_attributes(self, node): def get_attributes(self, node):
pass pass
...@@ -40,7 +40,7 @@ class HLSCustomOp(CustomOp): ...@@ -40,7 +40,7 @@ class HLSCustomOp(CustomOp):
@abstractmethod @abstractmethod
def code_generation(self, node): def code_generation(self, node):
pass pass
@abstractmethod @abstractmethod
def global_includes(self, node, code_gen_dict): def global_includes(self, node, code_gen_dict):
pass pass
...@@ -60,7 +60,7 @@ class HLSCustomOp(CustomOp): ...@@ -60,7 +60,7 @@ class HLSCustomOp(CustomOp):
@abstractmethod @abstractmethod
def docompute(self, node, code_gen_dict): def docompute(self, node, code_gen_dict):
pass pass
@abstractmethod @abstractmethod
def dataoutstrm(self, node, code_gen_dict): def dataoutstrm(self, node, code_gen_dict):
pass pass
...@@ -68,4 +68,3 @@ class HLSCustomOp(CustomOp): ...@@ -68,4 +68,3 @@ class HLSCustomOp(CustomOp):
@abstractmethod @abstractmethod
def save_as_npy(self, node, code_gen_dict): def save_as_npy(self, node, code_gen_dict):
pass pass
src/finn/custom_op/fpgadataflow/streamingmaxpool.py
+ 93
− 41
View file @ f7915ed7
import numpy as np
import onnx.helper as helper
import sys
import os import os
import subprocess import subprocess
from finn.core.datatype import DataType import numpy as np
from finn.core.utils import get_by_name from finn.core.utils import get_by_name
from finn.custom_op.fpgadataflow import HLSCustomOp from finn.custom_op.fpgadataflow import HLSCustomOp
...@@ -25,7 +23,9 @@ class StreamingMaxPool(HLSCustomOp): ...@@ -25,7 +23,9 @@ class StreamingMaxPool(HLSCustomOp):
in_ind += 1 in_ind += 1
self.code_generation(node) self.code_generation(node)
temp_files.append("execute_StreamingMaxPool.cpp") temp_files.append("execute_StreamingMaxPool.cpp")
bash_compile = """g++ -o execute_StreamingMaxPool execute_StreamingMaxPool.cpp /workspace/finn/cnpy/cnpy.cpp -I/workspace/finn/cnpy/ -I/workspace/finn/finn-hlslib -I/workspace/vivado-hlslib --std=c++11 -lz""" bash_compile = """g++ -o execute_StreamingMaxPool execute_StreamingMaxPool.cpp
/workspace/finn/cnpy/cnpy.cpp -I/workspace/finn/cnpy/
-I/workspace/finn/finn-hlslib -I/workspace/vivado-hlslib --std=c++11 -lz"""
process_compile = subprocess.Popen(bash_compile.split(), stdout=subprocess.PIPE) process_compile = subprocess.Popen(bash_compile.split(), stdout=subprocess.PIPE)
process_compile.communicate() process_compile.communicate()
bash_execute = "./execute_StreamingMaxPool" bash_execute = "./execute_StreamingMaxPool"
...@@ -34,18 +34,18 @@ class StreamingMaxPool(HLSCustomOp): ...@@ -34,18 +34,18 @@ class StreamingMaxPool(HLSCustomOp):
temp_files.append("execute_StreamingMaxPool") temp_files.append("execute_StreamingMaxPool")
temp_files.append("output.npy") temp_files.append("output.npy")
output = np.load("output.npy") output = np.load("output.npy")
context[node.output[0]]=output context[node.output[0]] = output
# deleting temporary files # deleting temporary files
for temp_file in temp_files: for temp_file in temp_files:
os.remove(temp_file) os.remove(temp_file)
def get_attributes(self, node): def get_attributes(self, node):
self.ImgDim = get_by_name(node.attribute, 'ImgDim').i self.ImgDim = get_by_name(node.attribute, "ImgDim").i
self.PoolDim = get_by_name(node.attribute, 'PoolDim').i self.PoolDim = get_by_name(node.attribute, "PoolDim").i
self.NumChannels = get_by_name(node.attribute, 'NumChannels').i self.NumChannels = get_by_name(node.attribute, "NumChannels").i
def code_generation(self, node): def code_generation(self, node):
code_gen_dict={} code_gen_dict = {}
self.get_attributes(node) self.get_attributes(node)
self.global_includes(node, code_gen_dict) self.global_includes(node, code_gen_dict)
self.defines(node, code_gen_dict) self.defines(node, code_gen_dict)
...@@ -54,27 +54,30 @@ class StreamingMaxPool(HLSCustomOp): ...@@ -54,27 +54,30 @@ class StreamingMaxPool(HLSCustomOp):
self.docompute(node, code_gen_dict) self.docompute(node, code_gen_dict)
self.dataoutstrm(node, code_gen_dict) self.dataoutstrm(node, code_gen_dict)
self.save_as_npy(node, code_gen_dict) self.save_as_npy(node, code_gen_dict)
template = self.docompute_template template = self.docompute_template
for key in code_gen_dict: for key in code_gen_dict:
#transform list into long string separated by '\n' # transform list into long string separated by '\n'
code_gen_line = "\n".join(code_gen_dict[key]) code_gen_line = "\n".join(code_gen_dict[key])
template = template.replace(key, code_gen_line) template = template.replace(key, code_gen_line)
f = open("execute_StreamingMaxPool.cpp", "w") f = open("execute_StreamingMaxPool.cpp", "w")
f.write(template) f.write(template)
f.close() f.close()
def global_includes(self, node, code_gen_dict): def global_includes(self, node, code_gen_dict):
code_gen_dict["$GLOBALS$"]=['#include "maxpool.h"'] code_gen_dict["$GLOBALS$"] = ['#include "maxpool.h"']
def defines(self, node, code_gen_dict): def defines(self, node, code_gen_dict):
code_gen_dict["$DEFINES$"]=['#define ImgDim {}\n #define PoolDim {}\n #define NumChannels {}'.format(self.ImgDim, self.PoolDim, self.NumChannels)] code_gen_dict["$DEFINES$"] = [
"#define ImgDim {}\n #define PoolDim {}\n #define NumChannels {}".format(
self.ImgDim, self.PoolDim, self.NumChannels
)
]
def read_npy_data(self, node, code_gen_dict): def read_npy_data(self, node, code_gen_dict):
code_gen_dict["$READNPYDATA$"]=[] code_gen_dict["$READNPYDATA$"] = []
input_ind = 0 input_ind = 0
input_file_names = [] input_file_names = []
for inputs in node.input: for inputs in node.input:
...@@ -83,39 +86,88 @@ class StreamingMaxPool(HLSCustomOp): ...@@ -83,39 +86,88 @@ class StreamingMaxPool(HLSCustomOp):
input_ind = 0 input_ind = 0
for input_file in input_file_names: for input_file in input_file_names:
code_gen_dict["$READNPYDATA$"].append('cnpy::NpyArray arr = cnpy::npy_load("{}");\n float* loaded_data{} = arr.data<float>();'.format(input_file, input_ind)) code_gen_dict["$READNPYDATA$"].append(
code_gen_dict["$READNPYDATA$"].append('int num_values = 1; \n for(int i = 0; i < arr.shape.size(); i++){\n num_values *= arr.shape[i]; \n }') """cnpy::NpyArray arr = cnpy::npy_load("{}");\n
code_gen_dict["$READNPYDATA$"].append('ap_uint<{}> dat;'.format(self.NumChannels)) float* loaded_data{} = arr.data<float>();""".format(
code_gen_dict["$READNPYDATA$"].append('for(int i=0; i < num_values/{}; i++){{'.format(self.NumChannels)) input_file, input_ind
)
)
code_gen_dict["$READNPYDATA$"].append(
""""int num_values = 1; \n
for(int i = 0; i < arr.shape.size(); i++){\n
num_values *= arr.shape[i]; \n }"""
)
code_gen_dict["$READNPYDATA$"].append(
"ap_uint<{}> dat;".format(self.NumChannels)
)
code_gen_dict["$READNPYDATA$"].append(
"for(int i=0; i < num_values/{}; i++){{".format(self.NumChannels)
)
for channel in range(self.NumChannels): for channel in range(self.NumChannels):
code_gen_dict["$READNPYDATA$"].append('dat.range({},{}) = loaded_data{}[i+((num_values/{})*{})];'.format(channel, channel, input_ind, self.NumChannels, channel)) code_gen_dict["$READNPYDATA$"].append(
code_gen_dict["$READNPYDATA$"].append('in{} << dat;'.format(input_ind)) "dat.range({},{}) = loaded_data{}[i+((num_values/{})*{})];".format(
code_gen_dict["$READNPYDATA$"].append('}') channel, channel, input_ind, self.NumChannels, channel
input_ind+=1 )
)
code_gen_dict["$READNPYDATA$"].append("in{} << dat;".format(input_ind))
code_gen_dict["$READNPYDATA$"].append("}")
input_ind += 1
def strm_decl(self, node, code_gen_dict): def strm_decl(self, node, code_gen_dict):
code_gen_dict["$STREAMDECLARATIONS$"]=[] code_gen_dict["$STREAMDECLARATIONS$"] = []
input_ind = 0 input_ind = 0
for inputs in node.input: for inputs in node.input:
code_gen_dict["$STREAMDECLARATIONS$"].append('hls::stream<ap_uint<{}>> in{} ("in{}");'.format(self.NumChannels, input_ind, input_ind)) code_gen_dict["$STREAMDECLARATIONS$"].append(
'hls::stream<ap_uint<{}>> in{} ("in{}");'.format(
self.NumChannels, input_ind, input_ind
)
)
input_ind += 1 input_ind += 1
code_gen_dict["$STREAMDECLARATIONS$"].append('hls::stream<ap_uint<{}>> out ("out");'.format(self.NumChannels)) code_gen_dict["$STREAMDECLARATIONS$"].append(
'hls::stream<ap_uint<{}>> out ("out");'.format(self.NumChannels)
)
def docompute(self, node, code_gen_dict): def docompute(self, node, code_gen_dict):
code_gen_dict["$DOCOMPUTE$"] = ['{}<ImgDim, PoolDim, NumChannels>(in0, out);'.format(node.op_type)] code_gen_dict["$DOCOMPUTE$"] = [
"{}<ImgDim, PoolDim, NumChannels>(in0, out);".format(node.op_type)
]
def dataoutstrm(self, node, code_gen_dict): def dataoutstrm(self, node, code_gen_dict):
code_gen_dict["$DATAOUTSTREAM$"]=['ap_uint<{}> out_data;\n std::vector<ap_uint<{}>> out_data_vector;'.format(self.NumChannels, self.NumChannels)] code_gen_dict["$DATAOUTSTREAM$"] = [
code_gen_dict["$DATAOUTSTREAM$"].append('while(out.read_nb(out_data)){') "ap_uint<{}> out_data;\n std::vector<ap_uint<{}>> out_data_vector;".format(
code_gen_dict["$DATAOUTSTREAM$"].append('out_data_vector.push_back(out_data);\n}') self.NumChannels, self.NumChannels
code_gen_dict["$DATAOUTSTREAM$"].append('std::vector<float> output_data_vector;') )
code_gen_dict["$DATAOUTSTREAM$"].append('for(std::vector<ap_uint<{}>>::iterator it = out_data_vector.begin(); it != out_data_vector.end(); ++it){{'.format(self.NumChannels)) ]
code_gen_dict["$DATAOUTSTREAM$"].append('ap_uint<{}> output_data = *it;'.format(self.NumChannels)) code_gen_dict["$DATAOUTSTREAM$"].append("while(out.read_nb(out_data)){")
code_gen_dict["$DATAOUTSTREAM$"].append(
"out_data_vector.push_back(out_data);\n}"
)
code_gen_dict["$DATAOUTSTREAM$"].append(
"std::vector<float> output_data_vector;"
)
code_gen_dict["$DATAOUTSTREAM$"].append(
"""for(std::vector<ap_uint<{}>>::iterator it = out_data_vector.begin();
it != out_data_vector.end(); ++it){{""".format(
self.NumChannels
)
)
code_gen_dict["$DATAOUTSTREAM$"].append(
"ap_uint<{}> output_data = *it;".format(self.NumChannels)
)
for channel in range(self.NumChannels): for channel in range(self.NumChannels):
code_gen_dict["$DATAOUTSTREAM$"].append('output_data_vector.push_back(output_data.range({},{}));'.format(channel, channel)) code_gen_dict["$DATAOUTSTREAM$"].append(
code_gen_dict["$DATAOUTSTREAM$"].append('}') "output_data_vector.push_back(output_data.range({},{}));".format(
channel, channel
)
)
code_gen_dict["$DATAOUTSTREAM$"].append("}")
def save_as_npy(self, node, code_gen_dict): def save_as_npy(self, node, code_gen_dict):
code_gen_dict["$SAVEASCNPY$"]=['cnpy::npy_save("output.npy",&output_data_vector[0],{{{},{},{}}},"w");'.format(self.NumChannels, int(self.ImgDim/self.PoolDim), int(self.ImgDim/self.PoolDim))] code_gen_dict["$SAVEASCNPY$"] = [
"""cnpy::npy_save("output.npy",&output_data_vector[0],
{{{},{},{}}},"w");""".format(
self.NumChannels,
int(self.ImgDim / self.PoolDim),
int(self.ImgDim / self.PoolDim),
)
]
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