def copy_propagate_update_analysis(stmt, var_dict, array_analysis):
"""update array analysis data during copy propagation.
If an array is in defs of a statement, we update its size variables.
"""
array_shape_classes = array_analysis.array_shape_classes
class_sizes = array_analysis.class_sizes
array_size_vars = array_analysis.array_size_vars
# find defs of stmt
def_set = set()
if isinstance(stmt, ir.Assign):
def_set.add(stmt.target.name)
for T, def_func in analysis.ir_extension_usedefs.items():
if isinstance(stmt, T):
_, def_set = def_func(stmt)
# update analysis for arrays in defs
for var in def_set:
if var in array_shape_classes:
if var in array_size_vars:
array_size_vars[var] = replace_vars_inner(array_size_vars[var],
var_dict)
shape_corrs = array_shape_classes[var]
for c in shape_corrs:
if c != -1:
class_sizes[c] = replace_vars_inner(
class_sizes[c], var_dict)
return
def apply_copies_sort(sort_node, var_dict, name_var_table, typemap, calltypes,
save_copies):
"""apply copy propagate in sort node"""
sort_node.key_arr = replace_vars_inner(sort_node.key_arr, var_dict)
for col_name in list(sort_node.df_vars.keys()):
sort_node.df_vars[col_name] = replace_vars_inner(
sort_node.df_vars[col_name], var_dict)
return
def apply_copies_filter(filter_node, var_dict, name_var_table, ext_func, ext_data,
typemap, calltypes, save_copies):
"""apply copy propagate in filter node"""
filter_node.bool_arr = replace_vars_inner(filter_node.bool_arr, var_dict)
for col_name in list(filter_node.df_in_vars.keys()):
filter_node.df_in_vars[col_name] = replace_vars_inner(filter_node.df_in_vars[col_name], var_dict)
for col_name in list(filter_node.df_out_vars.keys()):
filter_node.df_out_vars[col_name] = replace_vars_inner(filter_node.df_out_vars[col_name], var_dict)
return
def apply_copies_csv(csv_node, var_dict, name_var_table, typemap, calltypes, save_copies):
"""apply copy propagate in csv node"""
# update output_vars
new_out_vars = []
for col_var in csv_node.out_vars:
new_var = replace_vars_inner(col_var, var_dict)
new_out_vars.append(new_var)
csv_node.out_vars = new_out_vars
csv_node.file_name = replace_vars_inner(csv_node.file_name, var_dict)
return
def apply_copies_sort(sort_node, var_dict, name_var_table,
typemap, calltypes, save_copies):
"""apply copy propagate in sort node"""
for i in range(len(sort_node.key_arrs)):
sort_node.key_arrs[i] = replace_vars_inner(sort_node.key_arrs[i], var_dict)
sort_node.out_key_arrs[i] = replace_vars_inner(sort_node.out_key_arrs[i], var_dict)
for col_name in list(sort_node.df_in_vars.keys()):
sort_node.df_in_vars[col_name] = replace_vars_inner(
sort_node.df_in_vars[col_name], var_dict)
for col_name in list(sort_node.df_out_vars.keys()):
sort_node.df_out_vars[col_name] = replace_vars_inner(
sort_node.df_out_vars[col_name], var_dict)
return
def apply_copies_join(join_node, var_dict, name_var_table,
typemap, calltypes, save_copies):
"""apply copy propagate in join node"""
# left
for col_name in list(join_node.left_vars.keys()):
join_node.left_vars[col_name] = replace_vars_inner(
join_node.left_vars[col_name], var_dict)
# right
for col_name in list(join_node.right_vars.keys()):
join_node.right_vars[col_name] = replace_vars_inner(
join_node.right_vars[col_name], var_dict)
# output
for col_name in list(join_node.df_out_vars.keys()):
join_node.df_out_vars[col_name] = replace_vars_inner(
join_node.df_out_vars[col_name], var_dict)
return
