/usr/lib/python2.7/dist-packages/ffc/codegeneration.py is in python-ffc 2017.2.0.post0-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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"""
Compiler stage 4: Code generation
---------------------------------
This module implements the generation of C++ code for the body of each
UFC function from an (optimized) intermediate representation (OIR).
"""
# Copyright (C) 2009-2017 Anders Logg, Martin Sandve Alnæs, Marie E. Rognes,
# Kristian B. Oelgaard, and others
#
# This file is part of FFC.
#
# FFC is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# FFC is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with FFC. If not, see <http://www.gnu.org/licenses/>.
from itertools import chain
from ufl import product
# FFC modules
from ffc.log import info, begin, end, debug_code, dstr
# FFC code generation modules
from ffc.representation import pick_representation, ufc_integral_types
import ffc.uflacs.language.cnodes as L
from ffc.uflacs.language.format_lines import format_indented_lines
from ffc.uflacs.backends.ufc.utils import generate_error
from ffc.uflacs.backends.ufc.generators import ufc_integral, ufc_finite_element, ufc_dofmap, ufc_coordinate_mapping, ufc_form
def generate_code(ir, parameters):
"Generate code from intermediate representation."
begin("Compiler stage 4: Generating code")
full_ir = ir
# FIXME: This has global side effects
# Set code generation parameters
# set_float_formatting(parameters["precision"])
# set_exception_handling(parameters["convert_exceptions_to_warnings"])
# Extract representations
ir_finite_elements, ir_dofmaps, ir_coordinate_mappings, ir_integrals, ir_forms = ir
# Generate code for finite_elements
info("Generating code for %d finite_element(s)" % len(ir_finite_elements))
code_finite_elements = [_generate_finite_element_code(ir, parameters)
for ir in ir_finite_elements]
# Generate code for dofmaps
info("Generating code for %d dofmap(s)" % len(ir_dofmaps))
code_dofmaps = [_generate_dofmap_code(ir, parameters)
for ir in ir_dofmaps]
# Generate code for coordinate_mappings
info("Generating code for %d coordinate_mapping(s)" % len(ir_coordinate_mappings))
code_coordinate_mappings = [_generate_coordinate_mapping_code(ir, parameters)
for ir in ir_coordinate_mappings]
# Generate code for integrals
info("Generating code for integrals")
code_integrals = [_generate_integral_code(ir, parameters)
for ir in ir_integrals]
# Generate code for forms
info("Generating code for forms")
code_forms = [_generate_form_code(ir, parameters)
for ir in ir_forms]
# Extract additional includes
includes = _extract_includes(full_ir, code_integrals)
end()
return (code_finite_elements, code_dofmaps, code_coordinate_mappings,
code_integrals, code_forms, includes)
def _extract_includes(full_ir, code_integrals):
ir_finite_elements, ir_dofmaps, ir_coordinate_mappings, ir_integrals, ir_forms = full_ir
# Includes added by representations
includes = set()
for code in code_integrals:
includes.update(code["additional_includes_set"])
# Includes for dependencies in jit mode
jit = any(full_ir[i][j]["jit"]
for i in range(len(full_ir))
for j in range(len(full_ir[i])))
if jit:
dep_includes = set()
for ir in ir_finite_elements:
dep_includes.update(_finite_element_jit_includes(ir))
for ir in ir_dofmaps:
dep_includes.update(_dofmap_jit_includes(ir))
for ir in ir_coordinate_mappings:
dep_includes.update(_coordinate_mapping_jit_includes(ir))
#for ir in ir_integrals:
# dep_includes.update(_integral_jit_includes(ir))
for ir in ir_forms:
dep_includes.update(_form_jit_includes(ir))
includes.update(['#include "%s"' % inc for inc in dep_includes])
return includes
def _finite_element_jit_includes(ir):
classnames = ir["create_sub_element"]
postfix = "_finite_element"
return [classname.rpartition(postfix)[0] + ".h"
for classname in classnames]
def _dofmap_jit_includes(ir):
classnames = ir["create_sub_dofmap"]
postfix = "_dofmap"
return [classname.rpartition(postfix)[0] + ".h"
for classname in classnames]
def _coordinate_mapping_jit_includes(ir):
classnames = [
ir["coordinate_finite_element_classname"],
ir["scalar_coordinate_finite_element_classname"]
]
postfix = "_finite_element"
return [classname.rpartition(postfix)[0] + ".h"
for classname in classnames]
def _form_jit_includes(ir):
# Gather all header names for classes that are separately compiled
# For finite_element and dofmap the module and header name is the prefix,
# extracted here with .split, and equal for both classes so we skip dofmap here:
classnames = list(chain(
ir["create_finite_element"],
ir["create_coordinate_finite_element"]
))
postfix = "_finite_element"
includes = [classname.rpartition(postfix)[0] + ".h"
for classname in classnames]
classnames = ir["create_coordinate_mapping"]
postfix = "_coordinate_mapping"
includes += [classname.rpartition(postfix)[0] + ".h"
for classname in classnames]
return includes
tt_timing_template = """
// Initialize timing variables
static const std::size_t _tperiod = 10000;
static std::size_t _tcount = 0;
static auto _tsum = std::chrono::nanoseconds::zero();
static auto _tavg_best = std::chrono::nanoseconds::max();
static auto _tmin = std::chrono::nanoseconds::max();
static auto _tmax = std::chrono::nanoseconds::min();
// Measure single kernel time
auto _before = std::chrono::high_resolution_clock::now();
{ // Begin original kernel
%s
} // End original kernel
// Measure single kernel time
auto _after = std::chrono::high_resolution_clock::now();
// Update time stats
const std::chrono::seconds _s(1);
auto _tsingle = _after - _before;
++_tcount;
_tsum += _tsingle;
_tmin = std::min(_tmin, _tsingle);
_tmax = std::max(_tmax, _tsingle);
if (_tcount %% _tperiod == 0 || _tsum > _s)
{
// Record best average across batches
std::chrono::nanoseconds _tavg = _tsum / _tcount;
if (_tavg_best > _tavg)
_tavg_best = _tavg;
// Convert to ns
auto _tot_ns = std::chrono::duration_cast<std::chrono::nanoseconds>(_tsum).count();
auto _avg_ns = std::chrono::duration_cast<std::chrono::nanoseconds>(_tavg).count();
auto _min_ns = std::chrono::duration_cast<std::chrono::nanoseconds>(_tmin).count();
auto _max_ns = std::chrono::duration_cast<std::chrono::nanoseconds>(_tmax).count();
auto _avg_best_ns = std::chrono::duration_cast<std::chrono::nanoseconds>(_tavg_best).count();
// Print report
std::cout << "FFC tt time:"
<< " avg_best = " << _avg_best_ns << " ns,"
<< " avg = " << _avg_ns << " ns,"
<< " min = " << _min_ns << " ns,"
<< " max = " << _max_ns << " ns,"
<< " tot = " << _tot_ns << " ns,"
<< " n = " << _tcount
<< std::endl;
// Reset statistics for next batch
_tcount = 0;
_tsum = std::chrono::nanoseconds(0);
_tmin = std::chrono::nanoseconds::max();
_tmax = std::chrono::nanoseconds::min();
}
"""
def _generate_tabulate_tensor_comment(ir, parameters):
"Generate comment for tabulate_tensor."
r = ir["representation"]
integrals_metadata = ir["integrals_metadata"]
integral_metadata = ir["integral_metadata"]
comment = [ L.Comment("This function was generated using '%s' representation" % r),
L.Comment("with the following integrals metadata:"),
L.Comment(""),
L.Comment("\n".join(dstr(integrals_metadata).split("\n")[:-1]))
]
for i, metadata in enumerate(integral_metadata):
comment += [ L.Comment(""),
L.Comment("and the following integral %d metadata:" % i),
L.Comment(""),
L.Comment("\n".join(dstr(metadata).split("\n")[:-1]))
]
return format_indented_lines(L.StatementList(comment).cs_format(0), 1)
def _generate_integral_code(ir, parameters):
"Generate code for integrals from intermediate representation."
# Select representation
r = pick_representation(ir["representation"])
# Generate code
# TODO: Drop prefix argument and get from ir:
code = r.generate_integral_code(ir, ir["prefix"], parameters)
# Hack for benchmarking overhead in assembler with empty
# tabulate_tensor
if parameters["generate_dummy_tabulate_tensor"]:
code["tabulate_tensor"] = ""
# Wrapping tabulate_tensor in a timing snippet for benchmarking
if parameters["add_tabulate_tensor_timing"]:
code["tabulate_tensor"] = tt_timing_template % code["tabulate_tensor"]
code["additional_includes_set"] = code.get("additional_includes_set", set())
code["additional_includes_set"].add("#include <chrono>")
code["additional_includes_set"].add("#include <iostream>")
# Generate comment
code["tabulate_tensor_comment"] = _generate_tabulate_tensor_comment(ir, parameters)
return code
# TODO: Replace the above with this, currently something is not working
def _new_generate_integral_code(ir, parameters):
"Generate code for integrals from intermediate representation."
return ufc_integral(ir["integral_type"]).generate_snippets(L, ir, parameters)
def _generate_finite_element_code(ir, parameters):
"Generate code for finite_element from intermediate representation."
return ufc_finite_element().generate_snippets(L, ir, parameters)
def _generate_dofmap_code(ir, parameters):
"Generate code for dofmap from intermediate representation."
return ufc_dofmap().generate_snippets(L, ir, parameters)
def _generate_coordinate_mapping_code(ir, parameters):
"Generate code for coordinate_mapping from intermediate representation."
return ufc_coordinate_mapping().generate_snippets(L, ir, parameters)
def _generate_form_code(ir, parameters):
"Generate code for coordinate_mapping from intermediate representation."
return ufc_form().generate_snippets(L, ir, parameters)
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