def _create_gufunc_for_parfor_body(lowerer, parfor, typemap, typingctx,
targetctx, flags, locals, has_aliases,
index_var_typ, races):
'''
Takes a parfor and creates a gufunc function for its body.
There are two parts to this function.
1) Code to iterate across the iteration space as defined by the schedule.
2) The parfor body that does the work for a single point in the iteration space.
Part 1 is created as Python text for simplicity with a sentinel assignment to mark the point
in the IR where the parfor body should be added.
This Python text is 'exec'ed into existence and its IR retrieved with run_frontend.
The IR is scanned for the sentinel assignment where that basic block is split and the IR
for the parfor body inserted.
'''
loc = parfor.init_block.loc
# The parfor body and the main function body share ir.Var nodes.
# We have to do some replacements of Var names in the parfor body to make them
# legal parameter names. If we don't copy then the Vars in the main function also
# would incorrectly change their name.
loop_body = copy.copy(parfor.loop_body)
remove_dels(loop_body)
parfor_dim = len(parfor.loop_nests)
loop_indices = [l.index_variable.name for l in parfor.loop_nests]
# Get all the parfor params.
parfor_params = parfor.params
# Get just the outputs of the parfor.
parfor_outputs = numba.parfor.get_parfor_outputs(parfor, parfor_params)
# Get all parfor reduction vars, and operators.
parfor_redvars, parfor_reddict = numba.parfor.get_parfor_reductions(
parfor, parfor_params, lowerer.fndesc.calltypes)
# Compute just the parfor inputs as a set difference.
parfor_inputs = sorted(
list(set(parfor_params) - set(parfor_outputs) - set(parfor_redvars)))
races = races.difference(set(parfor_redvars))
for race in races:
warnings.warn_explicit(
"Variable %s used in parallel loop may be written "
"to simultaneously by multiple workers and may result "
"in non-deterministic or unintended results." % race,
ParallelSafetyWarning, loc.filename, loc.line)
replace_var_with_array(races, loop_body, typemap, lowerer.fndesc.calltypes)
if config.DEBUG_ARRAY_OPT == 1:
print("parfor_params = ", parfor_params, " ", type(parfor_params))
print("parfor_outputs = ", parfor_outputs, " ", type(parfor_outputs))
print("parfor_inputs = ", parfor_inputs, " ", type(parfor_inputs))
print("parfor_redvars = ", parfor_redvars, " ", type(parfor_redvars))
# Reduction variables are represented as arrays, so they go under
# different names.
parfor_redarrs = []
for var in parfor_redvars:
arr = var + "_arr"
parfor_redarrs.append(arr)
typemap[arr] = types.npytypes.Array(typemap[var], 1, "C")
# Reorder all the params so that inputs go first then outputs.
parfor_params = parfor_inputs + parfor_outputs + parfor_redarrs
if config.DEBUG_ARRAY_OPT == 1:
print("parfor_params = ", parfor_params, " ", type(parfor_params))
print("loop_indices = ", loop_indices, " ", type(loop_indices))
print("loop_body = ", loop_body, " ", type(loop_body))
_print_body(loop_body)
# Some Var are not legal parameter names so create a dict of potentially illegal
# param name to guaranteed legal name.
param_dict = legalize_names(parfor_params + parfor_redvars)
if config.DEBUG_ARRAY_OPT == 1:
print("param_dict = ", sorted(param_dict.items()), " ",
type(param_dict))
# Some loop_indices are not legal parameter names so create a dict of potentially illegal
# loop index to guaranteed legal name.
ind_dict = legalize_names(loop_indices)
# Compute a new list of legal loop index names.
legal_loop_indices = [ind_dict[v] for v in loop_indices]
if config.DEBUG_ARRAY_OPT == 1:
print("ind_dict = ", sorted(ind_dict.items()), " ", type(ind_dict))
print("legal_loop_indices = ", legal_loop_indices, " ",
type(legal_loop_indices))
for pd in parfor_params:
print("pd = ", pd)
print("pd type = ", typemap[pd], " ", type(typemap[pd]))
# Get the types of each parameter.
param_types = [typemap[v] for v in parfor_params]
# if config.DEBUG_ARRAY_OPT==1:
# param_types_dict = { v:typemap[v] for v in parfor_params }
# print("param_types_dict = ", param_types_dict, " ", type(param_types_dict))
# print("param_types = ", param_types, " ", type(param_types))
# Replace illegal parameter names in the loop body with legal ones.
replace_var_names(loop_body, param_dict)
# remember the name before legalizing as the actual arguments
parfor_args = parfor_params
# Change parfor_params to be legal names.
parfor_params = [param_dict[v] for v in parfor_params]
parfor_params_orig = parfor_params
parfor_params = []
ascontig = False
for pindex in range(len(parfor_params_orig)):
if ascontig and pindex < len(parfor_inputs) and isinstance(
param_types[pindex], types.npytypes.Array):
parfor_params.append(parfor_params_orig[pindex] + "param")
else:
parfor_params.append(parfor_params_orig[pindex])
# Change parfor body to replace illegal loop index vars with legal ones.
replace_var_names(loop_body, ind_dict)
loop_body_var_table = get_name_var_table(loop_body)
sentinel_name = get_unused_var_name("__sentinel__", loop_body_var_table)
if config.DEBUG_ARRAY_OPT == 1:
print("legal parfor_params = ", parfor_params, " ",
type(parfor_params))
# Determine the unique names of the scheduling and gufunc functions.
# sched_func_name = "__numba_parfor_sched_%s" % (hex(hash(parfor)).replace("-", "_"))
gufunc_name = "__numba_parfor_gufunc_%s" % (hex(hash(parfor)).replace(
"-", "_"))
if config.DEBUG_ARRAY_OPT:
# print("sched_func_name ", type(sched_func_name), " ", sched_func_name)
print("gufunc_name ", type(gufunc_name), " ", gufunc_name)
gufunc_txt = ""
# Create the gufunc function.
gufunc_txt += "def " + gufunc_name + \
"(sched, " + (", ".join(parfor_params)) + "):\n"
for pindex in range(len(parfor_inputs)):
if ascontig and isinstance(param_types[pindex], types.npytypes.Array):
gufunc_txt += (" " + parfor_params_orig[pindex] +
" = np.ascontiguousarray(" + parfor_params[pindex] +
")\n")
# Add initialization of reduction variables
for arr, var in zip(parfor_redarrs, parfor_redvars):
gufunc_txt += " " + param_dict[var] + \
"=" + param_dict[arr] + "[0]\n"
# For each dimension of the parfor, create a for loop in the generated gufunc function.
# Iterate across the proper values extracted from the schedule.
# The form of the schedule is start_dim0, start_dim1, ..., start_dimN, end_dim0,
# end_dim1, ..., end_dimN
for eachdim in range(parfor_dim):
for indent in range(eachdim + 1):
gufunc_txt += " "
sched_dim = eachdim
gufunc_txt += ("for " + legal_loop_indices[eachdim] +
" in range(sched[" + str(sched_dim) + "], sched[" +
str(sched_dim + parfor_dim) + "] + np.uint8(1)):\n")
if config.DEBUG_ARRAY_OPT_RUNTIME:
for indent in range(parfor_dim + 1):
gufunc_txt += " "
gufunc_txt += "print("
for eachdim in range(parfor_dim):
gufunc_txt += "\"" + legal_loop_indices[
eachdim] + "\"," + legal_loop_indices[eachdim] + ","
gufunc_txt += ")\n"
# Add the sentinel assignment so that we can find the loop body position
# in the IR.
for indent in range(parfor_dim + 1):
gufunc_txt += " "
gufunc_txt += sentinel_name + " = 0\n"
# Add assignments of reduction variables (for returning the value)
for arr, var in zip(parfor_redarrs, parfor_redvars):
gufunc_txt += " " + param_dict[arr] + \
"[0] = " + param_dict[var] + "\n"
gufunc_txt += " return None\n"
if config.DEBUG_ARRAY_OPT:
print("gufunc_txt = ", type(gufunc_txt), "\n", gufunc_txt)
# Force gufunc outline into existence.
globls = {"np": np}
locls = {}
exec_(gufunc_txt, globls, locls)
gufunc_func = locls[gufunc_name]
if config.DEBUG_ARRAY_OPT:
print("gufunc_func = ", type(gufunc_func), "\n", gufunc_func)
# Get the IR for the gufunc outline.
gufunc_ir = compiler.run_frontend(gufunc_func)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir dump ", type(gufunc_ir))
gufunc_ir.dump()
print("loop_body dump ", type(loop_body))
_print_body(loop_body)
# rename all variables in gufunc_ir afresh
var_table = get_name_var_table(gufunc_ir.blocks)
new_var_dict = {}
reserved_names = [sentinel_name] + \
list(param_dict.values()) + legal_loop_indices
for name, var in var_table.items():
if not (name in reserved_names):
new_var_dict[name] = mk_unique_var(name)
replace_var_names(gufunc_ir.blocks, new_var_dict)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir dump after renaming ")
gufunc_ir.dump()
gufunc_param_types = [numba.types.npytypes.Array(index_var_typ, 1, "C")
] + param_types
if config.DEBUG_ARRAY_OPT:
print("gufunc_param_types = ", type(gufunc_param_types), "\n",
gufunc_param_types)
gufunc_stub_last_label = max(gufunc_ir.blocks.keys()) + 1
# Add gufunc stub last label to each parfor.loop_body label to prevent
# label conflicts.
loop_body = add_offset_to_labels(loop_body, gufunc_stub_last_label)
# new label for splitting sentinel block
new_label = max(loop_body.keys()) + 1
# If enabled, add a print statement after every assignment.
if config.DEBUG_ARRAY_OPT_RUNTIME:
for label, block in loop_body.items():
new_block = block.copy()
new_block.clear()
loc = block.loc
scope = block.scope
for inst in block.body:
new_block.append(inst)
# Append print after assignment
if isinstance(inst, ir.Assign):
# Only apply to numbers
if typemap[inst.target.name] not in types.number_domain:
continue
# Make constant string
strval = "{} =".format(inst.target.name)
strconsttyp = types.Const(strval)
lhs = ir.Var(scope, mk_unique_var("str_const"), loc)
assign_lhs = ir.Assign(value=ir.Const(value=strval,
loc=loc),
target=lhs,
loc=loc)
typemap[lhs.name] = strconsttyp
new_block.append(assign_lhs)
# Make print node
print_node = ir.Print(args=[lhs, inst.target],
vararg=None,
loc=loc)
new_block.append(print_node)
sig = numba.typing.signature(types.none, typemap[lhs.name],
typemap[inst.target.name])
lowerer.fndesc.calltypes[print_node] = sig
loop_body[label] = new_block
if config.DEBUG_ARRAY_OPT:
print("parfor loop body")
_print_body(loop_body)
wrapped_blocks = wrap_loop_body(loop_body)
hoisted = hoist(parfor_params, loop_body, typemap, wrapped_blocks)
start_block = gufunc_ir.blocks[min(gufunc_ir.blocks.keys())]
start_block.body = start_block.body[:-1] + hoisted + [start_block.body[-1]]
unwrap_loop_body(loop_body)
if config.DEBUG_ARRAY_OPT:
print("After hoisting")
_print_body(loop_body)
# Search all the block in the gufunc outline for the sentinel assignment.
for label, block in gufunc_ir.blocks.items():
for i, inst in enumerate(block.body):
if isinstance(inst,
ir.Assign) and inst.target.name == sentinel_name:
# We found the sentinel assignment.
loc = inst.loc
scope = block.scope
# split block across __sentinel__
# A new block is allocated for the statements prior to the sentinel
# but the new block maintains the current block label.
prev_block = ir.Block(scope, loc)
prev_block.body = block.body[:i]
# The current block is used for statements after the sentinel.
block.body = block.body[i + 1:]
# But the current block gets a new label.
body_first_label = min(loop_body.keys())
# The previous block jumps to the minimum labelled block of the
# parfor body.
prev_block.append(ir.Jump(body_first_label, loc))
# Add all the parfor loop body blocks to the gufunc function's
# IR.
for (l, b) in loop_body.items():
gufunc_ir.blocks[l] = b
body_last_label = max(loop_body.keys())
gufunc_ir.blocks[new_label] = block
gufunc_ir.blocks[label] = prev_block
# Add a jump from the last parfor body block to the block containing
# statements after the sentinel.
gufunc_ir.blocks[body_last_label].append(
ir.Jump(new_label, loc))
break
else:
continue
break
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir last dump before renaming")
gufunc_ir.dump()
gufunc_ir.blocks = rename_labels(gufunc_ir.blocks)
remove_dels(gufunc_ir.blocks)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir last dump")
gufunc_ir.dump()
print("flags", flags)
print("typemap", typemap)
old_alias = flags.noalias
if not has_aliases:
if config.DEBUG_ARRAY_OPT:
print("No aliases found so adding noalias flag.")
flags.noalias = True
kernel_func = compiler.compile_ir(typingctx, targetctx, gufunc_ir,
gufunc_param_types, types.none, flags,
locals)
flags.noalias = old_alias
kernel_sig = signature(types.none, *gufunc_param_types)
if config.DEBUG_ARRAY_OPT:
print("kernel_sig = ", kernel_sig)
return kernel_func, parfor_args, kernel_sig
def _create_gufunc_for_parfor_body(lowerer, parfor, typemap, typingctx,
targetctx, flags, locals):
'''
Takes a parfor and creates a gufunc function for its body.
There are two parts to this function.
1) Code to iterate across the iteration space as defined by the schedule.
2) The parfor body that does the work for a single point in the iteration space.
Part 1 is created as Python text for simplicity with a sentinel assignment to mark the point
in the IR where the parfor body should be added.
This Python text is 'exec'ed into existence and its IR retrieved with run_frontend.
The IR is scanned for the sentinel assignment where that basic block is split and the IR
for the parfor body inserted.
'''
# TODO: need copy?
# The parfor body and the main function body share ir.Var nodes.
# We have to do some replacements of Var names in the parfor body to make them
# legal parameter names. If we don't copy then the Vars in the main function also
# would incorrectly change their name.
loop_body = copy.copy(parfor.loop_body)
parfor_dim = len(parfor.loop_nests)
loop_indices = [l.index_variable.name for l in parfor.loop_nests]
# Get all the parfor params.
parfor_params = parfor.params
# Get just the outputs of the parfor.
parfor_outputs = numba.parfor.get_parfor_outputs(parfor, parfor_params)
# Get all parfor reduction vars, and operators.
parfor_redvars, parfor_reddict = numba.parfor.get_parfor_reductions(
parfor, parfor_params, lowerer.fndesc.calltypes)
# Compute just the parfor inputs as a set difference.
parfor_inputs = sorted(
list(set(parfor_params) - set(parfor_outputs) - set(parfor_redvars)))
if config.DEBUG_ARRAY_OPT == 1:
print("parfor_params = ", parfor_params, " ", type(parfor_params))
print("parfor_outputs = ", parfor_outputs, " ", type(parfor_outputs))
print("parfor_inputs = ", parfor_inputs, " ", type(parfor_inputs))
print("parfor_redvars = ", parfor_redvars, " ", type(parfor_redvars))
# Reduction variables are represented as arrays, so they go under
# different names.
parfor_redarrs = []
for var in parfor_redvars:
arr = var + "_arr"
parfor_redarrs.append(arr)
typemap[arr] = types.npytypes.Array(typemap[var], 1, "C")
# Reorder all the params so that inputs go first then outputs.
parfor_params = parfor_inputs + parfor_outputs + parfor_redarrs
if config.DEBUG_ARRAY_OPT == 1:
print("parfor_params = ", parfor_params, " ", type(parfor_params))
#print("loop_ranges = ", loop_ranges, " ", type(loop_ranges))
print("loop_indices = ", loop_indices, " ", type(loop_indices))
print("loop_body = ", loop_body, " ", type(loop_body))
_print_body(loop_body)
# Some Var are not legal parameter names so create a dict of potentially illegal
# param name to guaranteed legal name.
param_dict = legalize_names(parfor_params + parfor_redvars)
if config.DEBUG_ARRAY_OPT == 1:
print("param_dict = ", sorted(param_dict.items()), " ",
type(param_dict))
# Some loop_indices are not legal parameter names so create a dict of potentially illegal
# loop index to guaranteed legal name.
ind_dict = legalize_names(loop_indices)
# Compute a new list of legal loop index names.
legal_loop_indices = [ind_dict[v] for v in loop_indices]
if config.DEBUG_ARRAY_OPT == 1:
print("ind_dict = ", sorted(ind_dict.items()), " ", type(ind_dict))
print("legal_loop_indices = ", legal_loop_indices, " ",
type(legal_loop_indices))
for pd in parfor_params:
print("pd = ", pd)
print("pd type = ", typemap[pd], " ", type(typemap[pd]))
# Get the types of each parameter.
param_types = [typemap[v] for v in parfor_params]
# if config.DEBUG_ARRAY_OPT==1:
# param_types_dict = { v:typemap[v] for v in parfor_params }
# print("param_types_dict = ", param_types_dict, " ", type(param_types_dict))
# print("param_types = ", param_types, " ", type(param_types))
# Replace illegal parameter names in the loop body with legal ones.
replace_var_names(loop_body, param_dict)
# remember the name before legalizing as the actual arguments
parfor_args = parfor_params
# Change parfor_params to be legal names.
parfor_params = [param_dict[v] for v in parfor_params]
# Change parfor body to replace illegal loop index vars with legal ones.
replace_var_names(loop_body, ind_dict)
if config.DEBUG_ARRAY_OPT == 1:
print("legal parfor_params = ", parfor_params, " ",
type(parfor_params))
# Determine the unique names of the scheduling and gufunc functions.
# sched_func_name = "__numba_parfor_sched_%s" % (hex(hash(parfor)).replace("-", "_"))
gufunc_name = "__numba_parfor_gufunc_%s" % (hex(hash(parfor)).replace(
"-", "_"))
if config.DEBUG_ARRAY_OPT:
# print("sched_func_name ", type(sched_func_name), " ", sched_func_name)
print("gufunc_name ", type(gufunc_name), " ", gufunc_name)
# Create the gufunc function.
gufunc_txt = "def " + gufunc_name + \
"(sched, " + (", ".join(parfor_params)) + "):\n"
# Add initialization of reduction variables
for arr, var in zip(parfor_redarrs, parfor_redvars):
gufunc_txt += " " + param_dict[var] + \
"=" + param_dict[arr] + "[0]\n"
# For each dimension of the parfor, create a for loop in the generated gufunc function.
# Iterate across the proper values extracted from the schedule.
# The form of the schedule is start_dim0, start_dim1, ..., start_dimN, end_dim0,
# end_dim1, ..., end_dimN
for eachdim in range(parfor_dim):
for indent in range(eachdim + 1):
gufunc_txt += " "
sched_dim = eachdim
gufunc_txt += ("for " + legal_loop_indices[eachdim] +
" in range(sched[" + str(sched_dim) + "], sched[" +
str(sched_dim + parfor_dim) + "] + 1):\n")
# Add the sentinel assignment so that we can find the loop body position
# in the IR.
for indent in range(parfor_dim + 1):
gufunc_txt += " "
gufunc_txt += "__sentinel__ = 0\n"
# Add assignments of reduction variables (for returning the value)
for arr, var in zip(parfor_redarrs, parfor_redvars):
gufunc_txt += " " + param_dict[arr] + \
"[0] = " + param_dict[var] + "\n"
gufunc_txt += " return None\n"
if config.DEBUG_ARRAY_OPT:
print("gufunc_txt = ", type(gufunc_txt), "\n", gufunc_txt)
# Force gufunc outline into existence.
exec(gufunc_txt)
gufunc_func = eval(gufunc_name)
if config.DEBUG_ARRAY_OPT:
print("gufunc_func = ", type(gufunc_func), "\n", gufunc_func)
# Get the IR for the gufunc outline.
gufunc_ir = compiler.run_frontend(gufunc_func)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir dump ", type(gufunc_ir))
gufunc_ir.dump()
print("loop_body dump ", type(loop_body))
_print_body(loop_body)
# rename all variables in gufunc_ir afresh
var_table = get_name_var_table(gufunc_ir.blocks)
new_var_dict = {}
reserved_names = ["__sentinel__"] + \
list(param_dict.values()) + legal_loop_indices
for name, var in var_table.items():
if not (name in reserved_names):
new_var_dict[name] = mk_unique_var(name)
replace_var_names(gufunc_ir.blocks, new_var_dict)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir dump after renaming ")
gufunc_ir.dump()
gufunc_param_types = [numba.types.npytypes.Array(numba.intp, 1, "C")
] + param_types
if config.DEBUG_ARRAY_OPT:
print("gufunc_param_types = ", type(gufunc_param_types), "\n",
gufunc_param_types)
gufunc_stub_last_label = max(gufunc_ir.blocks.keys())
# Add gufunc stub last label to each parfor.loop_body label to prevent
# label conflicts.
loop_body = add_offset_to_labels(loop_body, gufunc_stub_last_label)
# new label for splitting sentinel block
new_label = max(loop_body.keys()) + 1
if config.DEBUG_ARRAY_OPT:
_print_body(loop_body)
# Search all the block in the gufunc outline for the sentinel assignment.
for label, block in gufunc_ir.blocks.items():
for i, inst in enumerate(block.body):
if isinstance(inst,
ir.Assign) and inst.target.name == "__sentinel__":
# We found the sentinel assignment.
loc = inst.loc
scope = block.scope
# split block across __sentinel__
# A new block is allocated for the statements prior to the sentinel
# but the new block maintains the current block label.
prev_block = ir.Block(scope, loc)
prev_block.body = block.body[:i]
# The current block is used for statements after the sentinel.
block.body = block.body[i + 1:]
# But the current block gets a new label.
body_first_label = min(loop_body.keys())
# The previous block jumps to the minimum labelled block of the
# parfor body.
prev_block.append(ir.Jump(body_first_label, loc))
# Add all the parfor loop body blocks to the gufunc function's
# IR.
for (l, b) in loop_body.items():
gufunc_ir.blocks[l] = b
body_last_label = max(loop_body.keys())
gufunc_ir.blocks[new_label] = block
gufunc_ir.blocks[label] = prev_block
# Add a jump from the last parfor body block to the block containing
# statements after the sentinel.
gufunc_ir.blocks[body_last_label].append(
ir.Jump(new_label, loc))
break
else:
continue
break
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir last dump before renaming")
gufunc_ir.dump()
gufunc_ir.blocks = rename_labels(gufunc_ir.blocks)
remove_dels(gufunc_ir.blocks)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir last dump")
gufunc_ir.dump()
kernel_func = compiler.compile_ir(typingctx, targetctx, gufunc_ir,
gufunc_param_types, types.none, flags,
locals)
kernel_sig = signature(types.none, *gufunc_param_types)
if config.DEBUG_ARRAY_OPT:
print("kernel_sig = ", kernel_sig)
return kernel_func, parfor_args, kernel_sig
def _create_gufunc_for_parfor_body(
lowerer,
parfor,
typemap,
typingctx,
targetctx,
flags,
locals,
has_aliases,
index_var_typ):
'''
Takes a parfor and creates a gufunc function for its body.
There are two parts to this function.
1) Code to iterate across the iteration space as defined by the schedule.
2) The parfor body that does the work for a single point in the iteration space.
Part 1 is created as Python text for simplicity with a sentinel assignment to mark the point
in the IR where the parfor body should be added.
This Python text is 'exec'ed into existence and its IR retrieved with run_frontend.
The IR is scanned for the sentinel assignment where that basic block is split and the IR
for the parfor body inserted.
'''
# The parfor body and the main function body share ir.Var nodes.
# We have to do some replacements of Var names in the parfor body to make them
# legal parameter names. If we don't copy then the Vars in the main function also
# would incorrectly change their name.
loop_body = copy.copy(parfor.loop_body)
remove_dels(loop_body)
parfor_dim = len(parfor.loop_nests)
loop_indices = [l.index_variable.name for l in parfor.loop_nests]
# Get all the parfor params.
parfor_params = parfor.params
# Get just the outputs of the parfor.
parfor_outputs = numba.parfor.get_parfor_outputs(parfor, parfor_params)
# Get all parfor reduction vars, and operators.
parfor_redvars, parfor_reddict = numba.parfor.get_parfor_reductions(
parfor, parfor_params, lowerer.fndesc.calltypes)
# Compute just the parfor inputs as a set difference.
parfor_inputs = sorted(
list(
set(parfor_params) -
set(parfor_outputs) -
set(parfor_redvars)))
if config.DEBUG_ARRAY_OPT == 1:
print("parfor_params = ", parfor_params, " ", type(parfor_params))
print("parfor_outputs = ", parfor_outputs, " ", type(parfor_outputs))
print("parfor_inputs = ", parfor_inputs, " ", type(parfor_inputs))
print("parfor_redvars = ", parfor_redvars, " ", type(parfor_redvars))
# Reduction variables are represented as arrays, so they go under
# different names.
parfor_redarrs = []
for var in parfor_redvars:
arr = var + "_arr"
parfor_redarrs.append(arr)
typemap[arr] = types.npytypes.Array(typemap[var], 1, "C")
# Reorder all the params so that inputs go first then outputs.
parfor_params = parfor_inputs + parfor_outputs + parfor_redarrs
if config.DEBUG_ARRAY_OPT == 1:
print("parfor_params = ", parfor_params, " ", type(parfor_params))
print("loop_indices = ", loop_indices, " ", type(loop_indices))
print("loop_body = ", loop_body, " ", type(loop_body))
_print_body(loop_body)
# Some Var are not legal parameter names so create a dict of potentially illegal
# param name to guaranteed legal name.
param_dict = legalize_names(parfor_params + parfor_redvars)
if config.DEBUG_ARRAY_OPT == 1:
print(
"param_dict = ",
sorted(
param_dict.items()),
" ",
type(param_dict))
# Some loop_indices are not legal parameter names so create a dict of potentially illegal
# loop index to guaranteed legal name.
ind_dict = legalize_names(loop_indices)
# Compute a new list of legal loop index names.
legal_loop_indices = [ind_dict[v] for v in loop_indices]
if config.DEBUG_ARRAY_OPT == 1:
print("ind_dict = ", sorted(ind_dict.items()), " ", type(ind_dict))
print(
"legal_loop_indices = ",
legal_loop_indices,
" ",
type(legal_loop_indices))
for pd in parfor_params:
print("pd = ", pd)
print("pd type = ", typemap[pd], " ", type(typemap[pd]))
# Get the types of each parameter.
param_types = [typemap[v] for v in parfor_params]
# if config.DEBUG_ARRAY_OPT==1:
# param_types_dict = { v:typemap[v] for v in parfor_params }
# print("param_types_dict = ", param_types_dict, " ", type(param_types_dict))
# print("param_types = ", param_types, " ", type(param_types))
# Replace illegal parameter names in the loop body with legal ones.
replace_var_names(loop_body, param_dict)
# remember the name before legalizing as the actual arguments
parfor_args = parfor_params
# Change parfor_params to be legal names.
parfor_params = [param_dict[v] for v in parfor_params]
parfor_params_orig = parfor_params
parfor_params = []
ascontig = False
for pindex in range(len(parfor_params_orig)):
if ascontig and pindex < len(parfor_inputs) and isinstance(param_types[pindex], types.npytypes.Array):
parfor_params.append(parfor_params_orig[pindex]+"param")
else:
parfor_params.append(parfor_params_orig[pindex])
# Change parfor body to replace illegal loop index vars with legal ones.
replace_var_names(loop_body, ind_dict)
loop_body_var_table = get_name_var_table(loop_body)
sentinel_name = get_unused_var_name("__sentinel__", loop_body_var_table)
if config.DEBUG_ARRAY_OPT == 1:
print(
"legal parfor_params = ",
parfor_params,
" ",
type(parfor_params))
# Determine the unique names of the scheduling and gufunc functions.
# sched_func_name = "__numba_parfor_sched_%s" % (hex(hash(parfor)).replace("-", "_"))
gufunc_name = "__numba_parfor_gufunc_%s" % (
hex(hash(parfor)).replace("-", "_"))
if config.DEBUG_ARRAY_OPT:
# print("sched_func_name ", type(sched_func_name), " ", sched_func_name)
print("gufunc_name ", type(gufunc_name), " ", gufunc_name)
gufunc_txt = ""
# Create the gufunc function.
gufunc_txt += "def " + gufunc_name + \
"(sched, " + (", ".join(parfor_params)) + "):\n"
for pindex in range(len(parfor_inputs)):
if ascontig and isinstance(param_types[pindex], types.npytypes.Array):
gufunc_txt += (" " + parfor_params_orig[pindex]
+ " = np.ascontiguousarray(" + parfor_params[pindex] + ")\n")
# Add initialization of reduction variables
for arr, var in zip(parfor_redarrs, parfor_redvars):
gufunc_txt += " " + param_dict[var] + \
"=" + param_dict[arr] + "[0]\n"
# For each dimension of the parfor, create a for loop in the generated gufunc function.
# Iterate across the proper values extracted from the schedule.
# The form of the schedule is start_dim0, start_dim1, ..., start_dimN, end_dim0,
# end_dim1, ..., end_dimN
for eachdim in range(parfor_dim):
for indent in range(eachdim + 1):
gufunc_txt += " "
sched_dim = eachdim
gufunc_txt += ("for " +
legal_loop_indices[eachdim] +
" in range(sched[" +
str(sched_dim) +
"], sched[" +
str(sched_dim +
parfor_dim) +
"] + np.uint8(1)):\n")
if config.DEBUG_ARRAY_OPT_RUNTIME:
for indent in range(parfor_dim + 1):
gufunc_txt += " "
gufunc_txt += "print("
for eachdim in range(parfor_dim):
gufunc_txt += "\"" + legal_loop_indices[eachdim] + "\"," + legal_loop_indices[eachdim] + ","
gufunc_txt += ")\n"
# Add the sentinel assignment so that we can find the loop body position
# in the IR.
for indent in range(parfor_dim + 1):
gufunc_txt += " "
gufunc_txt += sentinel_name + " = 0\n"
# Add assignments of reduction variables (for returning the value)
for arr, var in zip(parfor_redarrs, parfor_redvars):
gufunc_txt += " " + param_dict[arr] + \
"[0] = " + param_dict[var] + "\n"
gufunc_txt += " return None\n"
if config.DEBUG_ARRAY_OPT:
print("gufunc_txt = ", type(gufunc_txt), "\n", gufunc_txt)
# Force gufunc outline into existence.
globls = {"np": np}
locls = {}
exec_(gufunc_txt, globls, locls)
gufunc_func = locls[gufunc_name]
if config.DEBUG_ARRAY_OPT:
print("gufunc_func = ", type(gufunc_func), "\n", gufunc_func)
# Get the IR for the gufunc outline.
gufunc_ir = compiler.run_frontend(gufunc_func)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir dump ", type(gufunc_ir))
gufunc_ir.dump()
print("loop_body dump ", type(loop_body))
_print_body(loop_body)
# rename all variables in gufunc_ir afresh
var_table = get_name_var_table(gufunc_ir.blocks)
new_var_dict = {}
reserved_names = [sentinel_name] + \
list(param_dict.values()) + legal_loop_indices
for name, var in var_table.items():
if not (name in reserved_names):
new_var_dict[name] = mk_unique_var(name)
replace_var_names(gufunc_ir.blocks, new_var_dict)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir dump after renaming ")
gufunc_ir.dump()
gufunc_param_types = [
numba.types.npytypes.Array(
index_var_typ, 1, "C")] + param_types
if config.DEBUG_ARRAY_OPT:
print(
"gufunc_param_types = ",
type(gufunc_param_types),
"\n",
gufunc_param_types)
gufunc_stub_last_label = max(gufunc_ir.blocks.keys()) + 1
# Add gufunc stub last label to each parfor.loop_body label to prevent
# label conflicts.
loop_body = add_offset_to_labels(loop_body, gufunc_stub_last_label)
# new label for splitting sentinel block
new_label = max(loop_body.keys()) + 1
# If enabled, add a print statement after every assignment.
if config.DEBUG_ARRAY_OPT_RUNTIME:
for label, block in loop_body.items():
new_block = block.copy()
new_block.clear()
loc = block.loc
scope = block.scope
for inst in block.body:
new_block.append(inst)
# Append print after assignment
if isinstance(inst, ir.Assign):
# Only apply to numbers
if typemap[inst.target.name] not in types.number_domain:
continue
# Make constant string
strval = "{} =".format(inst.target.name)
strconsttyp = types.Const(strval)
lhs = ir.Var(scope, mk_unique_var("str_const"), loc)
assign_lhs = ir.Assign(value=ir.Const(value=strval, loc=loc),
target=lhs, loc=loc)
typemap[lhs.name] = strconsttyp
new_block.append(assign_lhs)
# Make print node
print_node = ir.Print(args=[lhs, inst.target], vararg=None, loc=loc)
new_block.append(print_node)
sig = numba.typing.signature(types.none,
typemap[lhs.name],
typemap[inst.target.name])
lowerer.fndesc.calltypes[print_node] = sig
loop_body[label] = new_block
if config.DEBUG_ARRAY_OPT:
print("parfor loop body")
_print_body(loop_body)
wrapped_blocks = wrap_loop_body(loop_body)
hoisted = hoist(parfor_params, loop_body, typemap, wrapped_blocks)
start_block = gufunc_ir.blocks[min(gufunc_ir.blocks.keys())]
start_block.body = start_block.body[:-1] + hoisted + [start_block.body[-1]]
unwrap_loop_body(loop_body)
if config.DEBUG_ARRAY_OPT:
print("After hoisting")
_print_body(loop_body)
# Search all the block in the gufunc outline for the sentinel assignment.
for label, block in gufunc_ir.blocks.items():
for i, inst in enumerate(block.body):
if isinstance(
inst,
ir.Assign) and inst.target.name == sentinel_name:
# We found the sentinel assignment.
loc = inst.loc
scope = block.scope
# split block across __sentinel__
# A new block is allocated for the statements prior to the sentinel
# but the new block maintains the current block label.
prev_block = ir.Block(scope, loc)
prev_block.body = block.body[:i]
# The current block is used for statements after the sentinel.
block.body = block.body[i + 1:]
# But the current block gets a new label.
body_first_label = min(loop_body.keys())
# The previous block jumps to the minimum labelled block of the
# parfor body.
prev_block.append(ir.Jump(body_first_label, loc))
# Add all the parfor loop body blocks to the gufunc function's
# IR.
for (l, b) in loop_body.items():
gufunc_ir.blocks[l] = b
body_last_label = max(loop_body.keys())
gufunc_ir.blocks[new_label] = block
gufunc_ir.blocks[label] = prev_block
# Add a jump from the last parfor body block to the block containing
# statements after the sentinel.
gufunc_ir.blocks[body_last_label].append(
ir.Jump(new_label, loc))
break
else:
continue
break
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir last dump before renaming")
gufunc_ir.dump()
gufunc_ir.blocks = rename_labels(gufunc_ir.blocks)
remove_dels(gufunc_ir.blocks)
if config.DEBUG_ARRAY_OPT:
print("gufunc_ir last dump")
gufunc_ir.dump()
print("flags", flags)
print("typemap", typemap)
old_alias = flags.noalias
if not has_aliases:
if config.DEBUG_ARRAY_OPT:
print("No aliases found so adding noalias flag.")
flags.noalias = True
kernel_func = compiler.compile_ir(
typingctx,
targetctx,
gufunc_ir,
gufunc_param_types,
types.none,
flags,
locals)
flags.noalias = old_alias
kernel_sig = signature(types.none, *gufunc_param_types)
if config.DEBUG_ARRAY_OPT:
print("kernel_sig = ", kernel_sig)
return kernel_func, parfor_args, kernel_sig