def _ctc_check_compile(ctc_lib_path):
preambule = """
#include <string.h>
#include "ctc.h"
"""
body = """
ctcOptions options;
memset(&options, 0, sizeof(ctcOptions));
options.loc = CTC_CPU;
options.num_threads = 1;
"""
params = ['-I%s' % (os.path.dirname(__file__))]
if ctc_lib_path is not None:
params.extend(["-I%s" % (os.path.join(config.ctc.root, "include"))])
params.extend(["-L%s" % (ctc_lib_path)])
params.extend(["-l", "warpctc"])
compiler_res = GCC_compiler.try_flags(
params, preambule=preambule, body=body,
try_run=False, output=True)
avail, out, err = compiler_res if isinstance(compiler_res, tuple) else (compiler_res, None, None)
if not avail:
return False, ("cannot compile with warp-ctc. "
"We got this error:\n" + str(err))
return True, None
def _ctc_check_compile(ctc_lib_path):
preambule = """
#include <string.h>
#include "ctc.h"
"""
body = """
ctcOptions options;
memset(&options, 0, sizeof(ctcOptions));
options.loc = CTC_CPU;
options.num_threads = 1;
"""
params = ['-I%s' % (os.path.dirname(__file__))]
if ctc_lib_path is not None:
params.extend(["-I%s" % (os.path.join(config.ctc.root, "include"))])
params.extend(["-L%s" % (ctc_lib_path)])
params.extend(["-l", "warpctc"])
compiler_res = GCC_compiler.try_flags(
params, preambule=preambule, body=body,
try_run=False, output=True)
avail, out, err = compiler_res if isinstance(compiler_res, tuple) else (compiler_res, None, None)
if not avail:
return False, ("cannot compile with warp-ctc. "
"We got this error:\n" + str(err))
return True, None
def _dnn_check_compile():
preambule = """
#include <stdio.h>
#include <cudnn.h>
#include <cudnn_helper.h>
"""
# No need for the context in here since we won't execute that code
body = """
cudnnHandle_t _handle = NULL;
cudnnStatus_t err;
if ((err = cudnnCreate(&_handle)) != CUDNN_STATUS_SUCCESS) {
fprintf(stderr, "could not create cuDNN handle: %s",
cudnnGetErrorString(err));
return 1;
}
"""
params = ["-l", "cudnn", "-I" + os.path.dirname(__file__)]
if config.dnn.include_path:
params.append("-I" + config.dnn.include_path)
if config.dnn.library_path:
params.append("-L" + config.dnn.library_path)
# Do not run here the test program. It would run on the
# default gpu, not the one selected by the user. If mixed
# GPU are installed or if the GPUs are configured in
# exclusive mode, this cause bad detection.
avail, out, err = GCC_compiler.try_flags(
params, preambule=preambule, body=body,
try_run=False, output=True)
if not avail:
return False, ("Theano cannot compile with cuDNN. "
"We got this error:\n" + str(err))
return True, None
def _dnn_check_compile():
preambule = """
#include <stdio.h>
#include <cudnn.h>
#include <cudnn_helper.h>
"""
# No need for the context in here since we won't execute that code
body = """
cudnnHandle_t _handle = NULL;
cudnnStatus_t err;
if ((err = cudnnCreate(&_handle)) != CUDNN_STATUS_SUCCESS) {
fprintf(stderr, "could not create cuDNN handle: %s",
cudnnGetErrorString(err));
return 1;
}
"""
params = ["-l", "cudnn", "-I" + os.path.dirname(__file__)]
if config.dnn.include_path:
params.append("-I" + config.dnn.include_path)
if config.dnn.library_path:
params.append("-L" + config.dnn.library_path)
# Do not run here the test program. It would run on the
# default gpu, not the one selected by the user. If mixed
# GPU are installed or if the GPUs are configured in
# exclusive mode, this cause bad detection.
avail, out, err = GCC_compiler.try_flags(
params, preambule=preambule, body=body,
try_run=False, output=True)
if not avail:
return False, ("Theano cannot compile with cuDNN. "
"We got this error:\n" + str(err))
return True, None
def test_flag_detection():
# Check that the code detecting blas flags does not raise any exception.
# It used to happen on python 3 because of improper string handling,
# but was not detected because that path is not usually taken,
# so we test it here directly.
GCC_compiler.try_flags(["-lblas"])
def dnn_available():
if dnn_available.avail is not None:
return dnn_available.avail
if pygpu is None:
dnn_available.msg = "PyGPU not available"
dnn_available.avail = False
return False
if not init_dev.device.startswith('cuda'):
dnn_available.msg = "Not on a CUDA device. Got %s." % init_dev.device
dnn_available.avail = False
return False
# This is a hack because bin_id is in the from of
# "sm_<major><minor>" for cuda devices.
if pygpu.get_default_context().bin_id[:-2] < '30':
dnn_available.msg = "Device not supported by cuDNN"
dnn_available.avail = False
preambule = """
#include <stdio.h>
#include <cuda.h>
#include <cudnn.h>
#include <cudnn_helper.h>
"""
body = """
cudnnHandle_t _handle = NULL;
cudnnStatus_t err;
if ((err = cudnnCreate(&_handle)) != CUDNN_STATUS_SUCCESS) {
fprintf(stderr, "could not create cuDNN handle: %s",
cudnnGetErrorString(err));
return 1;
}
"""
# Do not run here the test program. It would run on the
# default gpu, not the one selected by the user. If mixed
# GPU are installed or if the GPUs are configured in
# exclusive mode, this cause bad detection.
comp, out, err = GCC_compiler.try_flags(
["-l", "cudnn", "-I" + os.path.dirname(__file__),
"-I" + config.dnn.include_path,
"-L" + config.dnn.library_path],
preambule=preambule, body=body,
try_run=False, output=True)
dnn_available.avail = comp
if not dnn_available.avail:
dnn_available.msg = (
"Theano cannot compile with cuDNN. We got this error:\n" +
str(err))
else:
# If we can compile, check that we can import and run.
v = version()
if v < 2000:
dnn_available.avail = False
dnn_available.msg = (
"You have an old release of CuDNN (or a release candidate) "
"that isn't supported. Please update to at least v2 final "
"version.")
raise RuntimeError(dnn_available.msg)
if v >= 3000 and v < 3007:
dnn_available.avail = False
dnn_available.msg = (
"You have installed a release candidate of CuDNN v3. This "
"isn't supported. Please update to v3 final version.")
raise RuntimeError(dnn_available.msg)
return dnn_available.avail
def test_flag_detection():
# Check that the code detecting blas flags does not raise any exception.
# It used to happen on python 3 because of improper string handling,
# but was not detected because that path is not usually taken,
# so we test it here directly.
GCC_compiler.try_flags(["-lblas"])
def dnn_available():
if dnn_available.avail is not None:
return dnn_available.avail
if pygpu is None:
dnn_available.msg = "PyGPU not available"
dnn_available.avail = False
return False
if not init_dev.device.startswith('cuda'):
dnn_available.msg = "Not on a CUDA device. Got %s." % init_dev.device
dnn_available.avail = False
return False
# This is a hack because bin_id is in the from of
# "sm_<major><minor>" for cuda devices.
if pygpu.get_default_context().bin_id[:-2] < '30':
dnn_available.msg = "Device not supported by cuDNN"
dnn_available.avail = False
preambule = """
#include <stdio.h>
#include <cudnn.h>
#include <cudnn_helper.h>
"""
body = """
cudnnHandle_t _handle = NULL;
cudnnStatus_t err;
if ((err = cudnnCreate(&_handle)) != CUDNN_STATUS_SUCCESS) {
fprintf(stderr, "could not create cuDNN handle: %s",
cudnnGetErrorString(err));
return 1;
}
"""
params = ["-l", "cudnn", "-I" + os.path.dirname(__file__)]
if config.dnn.include_path:
params.append("-I" + config.dnn.include_path)
if config.dnn.library_path:
params.append("-L" + config.dnn.library_path)
# Do not run here the test program. It would run on the
# default gpu, not the one selected by the user. If mixed
# GPU are installed or if the GPUs are configured in
# exclusive mode, this cause bad detection.
comp, out, err = GCC_compiler.try_flags(params,
preambule=preambule,
body=body,
try_run=False,
output=True)
dnn_available.avail = comp
if not dnn_available.avail:
dnn_available.msg = (
"Theano cannot compile with cuDNN. We got this error:\n" +
str(err))
else:
# If we can compile, check that we can import and run.
v = version()
if v < 2000:
dnn_available.avail = False
dnn_available.msg = (
"You have an old release of CuDNN (or a release candidate) "
"that isn't supported. Please update to at least v2 final "
"version.")
raise RuntimeError(dnn_available.msg)
if v >= 3000 and v < 3007:
dnn_available.avail = False
dnn_available.msg = (
"You have installed a release candidate of CuDNN v3. This "
"isn't supported. Please update to v3 final version.")
raise RuntimeError(dnn_available.msg)
return dnn_available.avail
