提交 e0ceda00 authored 作者: carriepl's avatar carriepl

Only verify if mitmot inputs have been reused in scan python backend

上级 e617dc50
...@@ -1175,9 +1175,9 @@ class Scan(PureOp): ...@@ -1175,9 +1175,9 @@ class Scan(PureOp):
offset = self.nit_sot_arg_offset + self.n_nit_sot offset = self.nit_sot_arg_offset + self.n_nit_sot
other_args = args[offset:] other_args = args[offset:]
input_storage = self.fn.input_storage input_storage = self.fn.input_storage
old_input_storage = [None] * len(input_storage) nb_mitmot_in = sum(map(len, self.tap_array[:self.n_mit_mot]))
old_input_data = [None] * len(input_storage) old_mitmot_input_storage = [None] * nb_mitmot_in
input_reused = [None] * len(input_storage) old_mitmot_input_data = [None] * nb_mitmot_in
output_storage = self.fn.output_storage output_storage = self.fn.output_storage
old_output_storage = [None] * len(output_storage) old_output_storage = [None] * len(output_storage)
old_output_data = [None] * len(output_storage) old_output_data = [None] * len(output_storage)
...@@ -1281,21 +1281,22 @@ class Scan(PureOp): ...@@ -1281,21 +1281,22 @@ class Scan(PureOp):
old_output_data[idx] = None old_output_data[idx] = None
# 4.6. Keep a reference to the variables (ndarrays, CudaNdarrays, # 4.6. Keep a reference to the variables (ndarrays, CudaNdarrays,
# etc) currently in the input_storage to be able to compare them # etc) associated with mitmot inputs currently in the
# with the content of the input_storage after the execution of the # input_storage to be able to compare them with the content of the
# function. Also keep pointers to their data to be able to detect # input_storage after the execution of the function. Also keep
# cases where outputs reused the allocated object but alter the # pointers to their data to be able to detect cases where outputs
# memory region they refer to. # reused the allocated object but alter the memory region they
for idx in xrange(len(input_storage)): # refer to.
var = input_storage[idx].storage[0] for idx in xrange(nb_mitmot_in):
old_input_storage[idx] = var var = input_storage[idx + self.n_seqs].storage[0]
old_mitmot_input_storage[idx] = var
if hasattr(var, 'gpudata'): if hasattr(var, 'gpudata'):
old_input_data[idx] = var.gpudata old_mitmot_input_data[idx] = var.gpudata
elif hasattr(var, 'data'): elif hasattr(var, 'data'):
old_input_data[idx] = var.data old_mitmot_input_data[idx] = var.data
else: else:
old_input_data[idx] = None old_mitmot_input_data[idx] = None
# 5.1 compute outputs # 5.1 compute outputs
t0_fn = time.time() t0_fn = time.time()
...@@ -1361,46 +1362,37 @@ class Scan(PureOp): ...@@ -1361,46 +1362,37 @@ class Scan(PureOp):
else: else:
output_reused[idx] = False output_reused[idx] = False
# 5.4 Check which of the input storage have been modified by the
# inner function
for idx in xrange(len(input_storage)):
# If the storage map does not contain the same object, then
# the pre-allocated output has not been reused
new_var = input_storage[idx].storage[0]
if old_input_storage[idx] is new_var:
# The pre-allocated output is only considered as having
# been reused if it still points to the same data as it
# did before the execution of the inner function
if old_input_data[idx] is None:
input_reused[idx] = False
else:
if hasattr(new_var, 'gpudata'):
input_reused[idx] = (new_var.gpudata ==
old_input_data[idx])
elif hasattr(new_var, 'data'):
input_reused[idx] = (new_var.data ==
old_input_data[idx])
else:
input_reused[idx] = False
t_fn += dt_fn t_fn += dt_fn
offset_out = 0 offset_out = 0
# 5.5 Copy over the values for mit_mot outputs # 5.4 Copy over the values for mit_mot outputs
mitmot_inp_offset = self.n_seqs mitmot_inp_offset = 0
mitmot_out_idx = 0 mitmot_out_idx = 0
for j in xrange(self.n_mit_mot): for j in xrange(self.n_mit_mot):
for k in self.mit_mot_out_slices[j]: for k in self.mit_mot_out_slices[j]:
if self.mitmots_preallocated[mitmot_out_idx]: if self.mitmots_preallocated[mitmot_out_idx]:
# This output tap has been preallocated. If the # This output tap has been preallocated.
# corresponding input storage has been replaced,
# recover the value as usual. Otherwise, the input was
# modified inplace and nothing needs to be done.
inp_idx = (mitmot_inp_offset + inp_idx = (mitmot_inp_offset +
self.tap_array[j].index(k)) self.tap_array[j].index(k))
if not input_reused[inp_idx]:
# Verify whether the input points to the same data as
# it did before the execution of the inner function.
old_var = old_mitmot_input_storage[inp_idx]
new_var = input_storage[self.n_seqs + inp_idx].storage[0]
if old_var is new_var:
old_data = old_mitmot_input_data[inp_idx]
if hasattr(new_var, 'gpudata'):
same_data = (new_var.gpudata == old_data)
elif hasattr(new_var, 'data'):
same_data = (new_var.data == old_data)
else:
same_data = False
# If the corresponding input storage still points to
# the same data, it has been modified inplace and
# nothing needs to be done. Otherwise, recover the
# and store it in `outs` as usual
if not same_data:
outs[j][0][k + pos[j]] = \ outs[j][0][k + pos[j]] = \
input_storage[inp_idx].storage[0] input_storage[inp_idx].storage[0]
...@@ -1415,7 +1407,7 @@ class Scan(PureOp): ...@@ -1415,7 +1407,7 @@ class Scan(PureOp):
mitmot_inp_offset += len(self.tap_array[j]) mitmot_inp_offset += len(self.tap_array[j])
# 5.6 Copy over the values for mit_sot/sit_sot outputs # 5.5 Copy over the values for mit_sot/sit_sot outputs
begin = self.n_mit_mot begin = self.n_mit_mot
end = self.n_outs end = self.n_outs
offset_out -= self.n_mit_mot offset_out -= self.n_mit_mot
...@@ -1426,7 +1418,7 @@ class Scan(PureOp): ...@@ -1426,7 +1418,7 @@ class Scan(PureOp):
outs[j][0][pos[j]] = \ outs[j][0][pos[j]] = \
output_storage[offset_out + j].storage[0] output_storage[offset_out + j].storage[0]
# 5.7 Copy over the values for nit_sot outputs # 5.6 Copy over the values for nit_sot outputs
begin = end begin = end
end += self.n_nit_sot end += self.n_nit_sot
for j in xrange(begin, end): for j in xrange(begin, end):
...@@ -1450,7 +1442,7 @@ class Scan(PureOp): ...@@ -1450,7 +1442,7 @@ class Scan(PureOp):
outs[j][0][pos[j]] = \ outs[j][0][pos[j]] = \
output_storage[j + offset_out].storage[0] output_storage[j + offset_out].storage[0]
# 5.8 Copy over the values for outputs corresponding to shared # 5.7 Copy over the values for outputs corresponding to shared
# variables # variables
begin = end begin = end
end += self.n_shared_outs end += self.n_shared_outs
......
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