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add reorder in mem estimator

pull/2364/head
oahzxl 2022-12-31 02:20:07 +08:00
parent e5a5fbb8a9
commit 966e4ea0cb
1 changed files with 32 additions and 11 deletions
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43
chunk_codegen.py
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@ -1040,11 +1040,13 @@ class IndexTracer(object):
chunk_info["region"][0] + len(chunk_info["args"]["prepose_nodes"]), chunk_info["region"][0] + len(chunk_info["args"]["prepose_nodes"]),
chunk_info["region"][1], chunk_info["region"][1],
) )
new_inputs_dim = []
for idx, input_dim in enumerate(chunk_info["inputs_dim"]): for idx, input_dim in enumerate(chunk_info["inputs_dim"]):
new_input_dim = {} new_input_dim = {}
for k, v in input_dim.items(): for k, v in input_dim.items():
new_input_dim[reorder_map[k]] = v new_input_dim[reorder_map[k]] = v
chunk_info["inputs_dim"][idx] = new_input_dim new_inputs_dim.append(new_input_dim)
chunk_info["inputs_dim"] = new_inputs_dim
return chunk_info return chunk_info
def _update_all_reorder_map(self, reorder_map): def _update_all_reorder_map(self, reorder_map):
@ -1095,11 +1097,24 @@ class IndexTracer(object):
for old_idx, new_idx in self.all_reorder_map.items(): for old_idx, new_idx in self.all_reorder_map.items():
new_node_list[new_idx] = node_list[old_idx] new_node_list[new_idx] = node_list[old_idx]
return new_node_list return new_node_list
def tmp_reorder(self, node_list, chunk_info):
if len(chunk_info["args"]["prepose_nodes"]) == 0:
return node_list, chunk_info
reorder_map = self._get_reorder_map(chunk_info)
# new tmp node list
new_node_list = [None for _ in range(len(node_list))]
for old_idx, new_idx in reorder_map.items():
new_node_list[new_idx] = node_list[old_idx]
chunk_info = self._reorder_chunk_info(chunk_info, reorder_map)
return new_node_list, chunk_info
class MemoryEstimator(object): class MemoryEstimator(object):
def __init__(self, index_tracer: IndexTracer) -> None: def __init__(self, index_tracer: IndexTracer) -> None:
self.index_tracer = index_tracer pass
def _get_meta_node_size(self, x): def _get_meta_node_size(self, x):
x = x.meta["tensor_meta"] x = x.meta["tensor_meta"]
@ -1453,9 +1468,11 @@ class ChunkSelector(object):
# get mem for chunk region # get mem for chunk region
regions_dict = [] regions_dict = []
for region in possible_chunk_regions: for region in possible_chunk_regions:
cur_chunk_infos = chunk_infos + [region] cur_region = region.copy()
cur_node_list, cur_region = self.index_tracer.tmp_reorder(self.index_tracer.node_list, cur_region)
cur_chunk_infos = chunk_infos + [cur_region]
cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem( cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem(
self.index_tracer.node_list, cur_chunk_infos cur_node_list, cur_chunk_infos
)[0] )[0]
cur_chunk_region_peak = cur_mem_peak[ cur_chunk_region_peak = cur_mem_peak[
max_chunk_region[0] : max_chunk_region[1] + 1 max_chunk_region[0] : max_chunk_region[1] + 1
@ -1492,9 +1509,11 @@ class ChunkSelector(object):
while cur_chunk_max_mem < self.max_memory: while cur_chunk_max_mem < self.max_memory:
chunk_size *= 2 chunk_size *= 2
chunk_info["chunk_size"] = chunk_size chunk_info["chunk_size"] = chunk_size
cur_chunk_infos = chunk_infos + [chunk_info] cur_chunk_info = chunk_info.copy()
cur_node_list, cur_chunk_info = self.index_tracer.tmp_reorder(self.index_tracer.node_list, cur_chunk_info)
cur_chunk_infos = chunk_infos + [cur_chunk_info]
cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem( cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem(
self.index_tracer.node_list, cur_chunk_infos cur_node_list, cur_chunk_infos
)[0] )[0]
cur_chunk_max_mem = max( cur_chunk_max_mem = max(
cur_mem_peak[chunk_info["region"][0] : chunk_info["region"][1] + 1] cur_mem_peak[chunk_info["region"][0] : chunk_info["region"][1] + 1]
@ -1511,11 +1530,13 @@ class ChunkSelector(object):
else: else:
gap = 1 gap = 1
while r >= l + gap: while r >= l + gap:
mid = int(l + (r - l) / 2) mid = int((l + r) / 2 + 0.5)
chunk_info["chunk_size"] = mid chunk_info["chunk_size"] = mid
cur_chunk_infos = chunk_infos + [chunk_info] cur_chunk_info = chunk_info.copy()
cur_node_list, cur_chunk_info = self.index_tracer.tmp_reorder(self.index_tracer.node_list, cur_chunk_info)
cur_chunk_infos = chunk_infos + [cur_chunk_info]
cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem( cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem(
self.index_tracer.node_list, cur_chunk_infos cur_node_list, cur_chunk_infos
)[0] )[0]
cur_chunk_max_mem = max( cur_chunk_max_mem = max(
cur_mem_peak[chunk_info["region"][0] : chunk_info["region"][1] + 1] cur_mem_peak[chunk_info["region"][0] : chunk_info["region"][1] + 1]
@ -1529,7 +1550,7 @@ class ChunkSelector(object):
def _get_compute_node_num(self, start, end): def _get_compute_node_num(self, start, end):
count = 0 count = 0
for i in self.index_tracer.node_list[start : end + 1]: for i in self.index_tracer.node_list[start : end + 1]:
if _is_non_compute_node(i): if not _is_non_compute_node(i):
count += 1 count += 1
return count return count
@ -1547,7 +1568,7 @@ class ChunkSelector(object):
max_region_range = 0 max_region_range = 0
best_region = None best_region = None
if best_region is not None: if best_region is not None:
best_region["chunk_size"] = 2 best_region["chunk_size"] = 1
return best_region return best_region
def _is_legal_region(self, cur_chunk_info, chunk_infos): def _is_legal_region(self, cur_chunk_info, chunk_infos):