mirror of https://github.com/hpcaitech/ColossalAI
rename trace_index to trace_indice
parent
065f0b4c27
commit
0ea903b94e
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@ -94,9 +94,9 @@ def _replace_reshape_size(context, node_name, reshape_size_dict):
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return context
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def _replace_ones_like(search_chunk, chunk_infos, region_idx, node_idx, node, body):
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def _replace_ones_like(search_chunk: SearchChunk, chunk_infos, region_idx, node_idx, node, body):
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if "ones_like" in node.name:
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meta_node = search_chunk.trace_index.node_list[node_idx]
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meta_node = search_chunk.trace_indice.node_list[node_idx]
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chunk_dim = chunk_infos[region_idx]["node_chunk_dim"][meta_node]["chunk_dim"]
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if get_node_shape(meta_node)[chunk_dim] != 1:
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source_node = meta_node.args[0].args[0]
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@ -1,22 +1,22 @@
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from .trace_index import TraceIndex
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from .trace_indice import TraceIndice
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from .utils import find_idx_by_name
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class ReorderGraph(object):
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def __init__(self, trace_index: TraceIndex) -> None:
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self.trace_index = trace_index
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def __init__(self, trace_indice: TraceIndice) -> None:
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self.trace_indice = trace_indice
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self.all_reorder_map = {
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i: i for i in range(len(self.trace_index.idx_trace_list))
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i: i for i in range(len(self.trace_indice.idx_trace_list))
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}
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def _get_reorder_map(self, chunk_info):
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reorder_map = {i: i for i in range(len(self.trace_index.node_list))}
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reorder_map = {i: i for i in range(len(self.trace_indice.node_list))}
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chunk_region_start = chunk_info["region"][0]
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chunk_region_end = chunk_info["region"][1]
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chunk_prepose_nodes = chunk_info["args"]["prepose_nodes"]
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chunk_prepose_nodes_idx = [
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find_idx_by_name(i.name, self.trace_index.node_list)
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find_idx_by_name(i.name, self.trace_indice.node_list)
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for i in chunk_prepose_nodes
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]
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# put prepose nodes ahead
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@ -24,10 +24,10 @@ class ReorderGraph(object):
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n_idx = chunk_prepose_nodes_idx[idx]
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reorder_map[n_idx] = chunk_region_start + idx
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# put other nodes after prepose nodes
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for n in self.trace_index.node_list[chunk_region_start : chunk_region_end + 1]:
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for n in self.trace_indice.node_list[chunk_region_start : chunk_region_end + 1]:
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if n in chunk_prepose_nodes:
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continue
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n_idx = find_idx_by_name(n.name, self.trace_index.node_list)
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n_idx = find_idx_by_name(n.name, self.trace_indice.node_list)
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pos = sum([n_idx < i for i in chunk_prepose_nodes_idx])
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reorder_map[n_idx] = n_idx + pos
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@ -53,25 +53,25 @@ class ReorderGraph(object):
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self.all_reorder_map[origin_idx] = reorder_map[map_idx]
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def _reorder_self_node_list(self, reorder_map):
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new_node_list = [None for _ in range(len(self.trace_index.node_list))]
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new_node_list = [None for _ in range(len(self.trace_indice.node_list))]
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for old_idx, new_idx in reorder_map.items():
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new_node_list[new_idx] = self.trace_index.node_list[old_idx]
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self.trace_index.node_list = new_node_list
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new_node_list[new_idx] = self.trace_indice.node_list[old_idx]
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self.trace_indice.node_list = new_node_list
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def _reorder_idx_trace(self, reorder_map):
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# reorder list
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new_idx_trace_list = [None for _ in range(len(self.trace_index.idx_trace_list))]
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new_idx_trace_list = [None for _ in range(len(self.trace_indice.idx_trace_list))]
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for old_idx, new_idx in reorder_map.items():
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new_idx_trace_list[new_idx] = self.trace_index.idx_trace_list[old_idx]
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self.trace_index.idx_trace_list = new_idx_trace_list
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new_idx_trace_list[new_idx] = self.trace_indice.idx_trace_list[old_idx]
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self.trace_indice.idx_trace_list = new_idx_trace_list
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# update compute
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for idx_trace in self.trace_index.idx_trace_list:
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for idx_trace in self.trace_indice.idx_trace_list:
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compute = idx_trace["compute"]
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for dim_compute in compute:
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for idx, i in enumerate(dim_compute):
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dim_compute[idx] = reorder_map[i]
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# update source
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for idx_trace in self.trace_index.idx_trace_list:
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for idx_trace in self.trace_indice.idx_trace_list:
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source = idx_trace["source"]
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for dim_idx, dim_source in enumerate(source):
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new_dim_source = {}
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@ -7,7 +7,7 @@ from .estimate_memory import EstimateMemory
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from .reorder_graph import ReorderGraph
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from .select_chunk import SelectChunk
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from .trace_flow import TraceFlow
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from .trace_index import TraceIndex
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from .trace_indice import TraceIndice
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from .utils import (
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get_node_shape,
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is_non_compute_node,
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@ -47,13 +47,13 @@ class SearchChunk(object):
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def __init__(self, gm, max_memory=None, print_mem=False) -> None:
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self.gm = gm
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self.print_mem = print_mem
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self.trace_index = TraceIndex(list(gm.graph.nodes))
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self.trace_index.trace_index()
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self.trace_flow = TraceFlow(self.trace_index)
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self.reorder_graph = ReorderGraph(self.trace_index)
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self.trace_indice = TraceIndice(list(gm.graph.nodes))
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self.trace_indice.trace_index()
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self.trace_flow = TraceFlow(self.trace_indice)
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self.reorder_graph = ReorderGraph(self.trace_indice)
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self.estimate_memory = EstimateMemory()
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self.select_chunk = SelectChunk(
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self.trace_index,
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self.trace_indice,
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self.estimate_memory,
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self.reorder_graph,
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max_memory=max_memory,
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@ -72,7 +72,7 @@ class SearchChunk(object):
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free_var_idx (List): all indexs of free vars
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"""
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free_var_idx = []
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for idx, n in enumerate(self.trace_index.node_list):
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for idx, n in enumerate(self.trace_indice.node_list):
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if n.op == "placeholder":
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free_var_idx.append(idx)
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return free_var_idx
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@ -156,7 +156,7 @@ class SearchChunk(object):
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"""
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start_traces = input_trace[start_idx]
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end_trace = output_trace[end_idx]
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end_node = self.trace_index.node_list[end_idx]
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end_node = self.trace_indice.node_list[end_idx]
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chunk_infos = []
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for end_dim, _ in enumerate(end_trace["idx"]):
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if len(start_traces) > 1:
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@ -205,23 +205,23 @@ class SearchChunk(object):
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possible_chunk_region (List)
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"""
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possible_chunk_region = []
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output_trace = copy.deepcopy(self.trace_index.idx_trace_list)
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output_trace = copy.deepcopy(self.trace_indice.idx_trace_list)
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input_trace = [] # trace of a node's input nodes
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for _, n in enumerate(self.trace_index.node_list):
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for _, n in enumerate(self.trace_indice.node_list):
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cur_trace = {}
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for arg in n.args:
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if type(arg) == type(n) and not is_non_compute_node_except_placeholder(
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arg
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):
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cur_trace[arg] = self.trace_index._find_trace_from_node(arg)
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cur_trace[arg] = self.trace_indice._find_trace_from_node(arg)
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input_trace.append(cur_trace)
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for start_idx in range(max_chunk_region[0], peak_node + 1):
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for end_idx in range(peak_node, max_chunk_region[1] + 1):
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# skip non compute nodes
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if is_non_compute_node(
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self.trace_index.node_list[start_idx]
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) or is_non_compute_node(self.trace_index.node_list[end_idx]):
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self.trace_indice.node_list[start_idx]
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) or is_non_compute_node(self.trace_indice.node_list[end_idx]):
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continue
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# select free dim
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@ -292,7 +292,7 @@ class SearchChunk(object):
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_,
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active_node,
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) = self.estimate_memory.estimate_chunk_inference_mem(
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self.trace_index.node_list
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self.trace_indice.node_list
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)
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mem_peak = init_mem_peak
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@ -307,13 +307,13 @@ class SearchChunk(object):
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_,
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active_node,
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) = self.estimate_memory.estimate_chunk_inference_mem(
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self.trace_index.node_list, chunk_infos
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self.trace_indice.node_list, chunk_infos
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)
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if self._stop_search(init_mem_peak, mem_peak):
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break
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if self.print_mem:
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self.print_mem = False
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self.estimate_memory.estimate_chunk_inference_mem(
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self.trace_index.node_list, chunk_infos, print_mem=True
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self.trace_indice.node_list, chunk_infos, print_mem=True
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)
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return chunk_infos
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@ -1,19 +1,19 @@
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from .estimate_memory import EstimateMemory
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from .reorder_graph import ReorderGraph
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from .trace_index import TraceIndex
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from .trace_indice import TraceIndice
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from .utils import is_non_compute_node
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class SelectChunk(object):
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def __init__(
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self,
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trace_index: TraceIndex,
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trace_indice: TraceIndice,
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estimate_memory: EstimateMemory,
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reorder_graph: ReorderGraph,
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max_memory=None,
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):
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self.index_tracer = trace_index
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self.memory_estimator = estimate_memory
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self.trace_indice = trace_indice
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self.estimate_memory = estimate_memory
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self.reorder_graph = reorder_graph
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if max_memory is not None:
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self.stratge = "fit_memory"
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@ -68,10 +68,10 @@ class SelectChunk(object):
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for region in possible_chunk_regions:
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cur_region = region.copy()
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cur_node_list, cur_region = self.reorder_graph.tmp_reorder(
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self.index_tracer.node_list, cur_region
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self.trace_indice.node_list, cur_region
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)
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cur_chunk_infos = chunk_infos + [cur_region]
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cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem(
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cur_mem_peak = self.estimate_memory.estimate_chunk_inference_mem(
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cur_node_list, cur_chunk_infos
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)[0]
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cur_chunk_region_peak = cur_mem_peak[
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@ -113,7 +113,7 @@ class SelectChunk(object):
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chunk_size *= 2
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reorder_chunk_info["chunk_size"] = chunk_size
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cur_chunk_infos = chunk_infos + [reorder_chunk_info]
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cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem(
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cur_mem_peak = self.estimate_memory.estimate_chunk_inference_mem(
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chunk_region_dict["reorder_node_list"], cur_chunk_infos
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)[0]
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cur_chunk_max_mem = max(
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@ -139,7 +139,7 @@ class SelectChunk(object):
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mid = int((left + right) / 2 + 0.5)
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chunk_info["chunk_size"] = mid
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cur_chunk_infos = chunk_infos + [chunk_info]
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cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem(
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cur_mem_peak = self.estimate_memory.estimate_chunk_inference_mem(
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chunk_region_dict["reorder_node_list"], cur_chunk_infos
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)[0]
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cur_chunk_max_mem = max(
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@ -153,7 +153,7 @@ class SelectChunk(object):
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def _get_compute_node_num(self, start, end):
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count = 0
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for i in self.index_tracer.node_list[start : end + 1]:
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for i in self.trace_indice.node_list[start : end + 1]:
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if not is_non_compute_node(i):
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count += 1
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return count
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@ -178,10 +178,10 @@ class SelectChunk(object):
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for region in possible_chunk_regions:
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cur_region = region.copy()
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cur_node_list, cur_region = self.reorder_graph.tmp_reorder(
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self.index_tracer.node_list, cur_region
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self.trace_indice.node_list, cur_region
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)
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cur_chunk_infos = chunk_infos + [cur_region]
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cur_mem_peak = self.memory_estimator.estimate_chunk_inference_mem(
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cur_mem_peak = self.estimate_memory.estimate_chunk_inference_mem(
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cur_node_list, cur_chunk_infos
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)[0]
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cur_chunk_region_peak = cur_mem_peak[
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@ -1,4 +1,4 @@
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from .trace_index import TraceIndex
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from .trace_indice import TraceIndice
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from .utils import (
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find_chunk_all_input_nodes,
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find_chunk_compute_input_and_output_nodes,
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@ -10,8 +10,8 @@ from .utils import (
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class TraceFlow(object):
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def __init__(self, trace_index: TraceIndex) -> None:
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self.trace_index = trace_index
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def __init__(self, trace_indice: TraceIndice) -> None:
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self.trace_indice = trace_indice
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def check_index_source(self, start_dim, start_node, start_idx, end_dim, end_node):
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"""
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Returns:
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bool: True if check pass
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"""
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start_node_idx = find_idx_by_name(start_node.name, self.trace_index.node_list)
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end_node_trace = self.trace_index._find_trace_from_node(end_node)
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start_node_idx = find_idx_by_name(start_node.name, self.trace_indice.node_list)
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end_node_trace = self.trace_indice._find_trace_from_node(end_node)
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end_node_trace_source = end_node_trace["source"][end_dim]
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sorted_source = sorted(
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end_node_trace_source.items(), key=lambda d: d[0], reverse=True
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@ -51,24 +51,24 @@ class TraceFlow(object):
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Returns:
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bool: True if check pass
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"""
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end_node_trace = self.trace_index._find_trace_from_node(end_node)
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end_node_trace = self.trace_indice._find_trace_from_node(end_node)
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end_node_compute = end_node_trace["compute"][end_dim]
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if any(start_idx <= i <= end_idx for i in end_node_compute):
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return False
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return True
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def get_node_chunk_dim(self, node_from, node_from_dim, node_to):
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node_from_source = self.trace_index._find_source_trace_from_node(node_from)
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node_from_source = self.trace_indice._find_source_trace_from_node(node_from)
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dim_source = node_from_source[node_from_dim]
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node_to_idx = find_idx_by_name(node_to.name, self.trace_index.node_list)
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node_to_idx = find_idx_by_name(node_to.name, self.trace_indice.node_list)
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for k, v in dim_source.items():
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if k == node_to_idx:
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return v
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return None
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def _find_inherit_dim(self, input_node, input_dim, node):
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input_node_idx = find_idx_by_name(input_node.name, self.trace_index.node_list)
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node_trace_source = self.trace_index._find_source_trace_from_node(node)
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input_node_idx = find_idx_by_name(input_node.name, self.trace_indice.node_list)
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node_trace_source = self.trace_indice._find_source_trace_from_node(node)
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for node_dim in range(len(get_node_shape(node))):
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if (
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input_node_idx in node_trace_source[node_dim]
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@ -82,19 +82,19 @@ class TraceFlow(object):
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for input_node_idx, input_node in enumerate(chunk_infos["inputs"]):
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for k, v in chunk_infos["inputs_dim"][input_node_idx].items():
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inherit_dim = self._find_inherit_dim(
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input_node, v, self.trace_index.node_list[k]
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input_node, v, self.trace_indice.node_list[k]
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)
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if inherit_dim:
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input_dim_after_node[k] = inherit_dim
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for node in self.trace_index.node_list[
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for node in self.trace_indice.node_list[
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chunk_infos["region"][0] : chunk_infos["region"][1] + 1
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]:
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if is_non_compute_node_except_placeholder(node):
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continue
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count = 0
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duplicate_dims = []
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node_trace_source = self.trace_index._find_source_trace_from_node(node)
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node_trace_source = self.trace_indice._find_source_trace_from_node(node)
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for node_dim in range(len(get_node_shape(node))):
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duplicate_dim = []
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duplicate_flag = False
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@ -130,7 +130,7 @@ class TraceFlow(object):
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all_node_info,
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next_node_list,
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):
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arg_idx = find_idx_by_name(arg_node.name, self.trace_index.node_list)
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arg_idx = find_idx_by_name(arg_node.name, self.trace_indice.node_list)
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# arg in chunk range or be inputs
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if not (start_idx <= arg_idx < end_idx):
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return True
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@ -171,7 +171,7 @@ class TraceFlow(object):
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def _get_all_node_info(self, end_dim, start_idx, end_idx):
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cur_node_list = [
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self.trace_index.node_list[end_idx]
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self.trace_indice.node_list[end_idx]
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] # start from the last node
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all_node_info = {cur_node_list[0]: {"chunk_dim": end_dim, "fix_dim": []}}
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@ -183,10 +183,10 @@ class TraceFlow(object):
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cur_node_chunk_dim = all_node_info[cur_node]["chunk_dim"]
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cur_node_fix_dim = all_node_info[cur_node]["fix_dim"]
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if cur_node_chunk_dim:
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cur_node_compute = self.trace_index._find_compute_trace_from_node(
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cur_node_compute = self.trace_indice._find_compute_trace_from_node(
|
||||
cur_node
|
||||
)
|
||||
cur_node_source = self.trace_index._find_source_trace_from_node(
|
||||
cur_node_source = self.trace_indice._find_source_trace_from_node(
|
||||
cur_node
|
||||
)
|
||||
else:
|
||||
|
@ -220,7 +220,7 @@ class TraceFlow(object):
|
|||
if not (
|
||||
start_idx
|
||||
<= find_idx_by_name(
|
||||
arg.name, self.trace_index.node_list
|
||||
arg.name, self.trace_indice.node_list
|
||||
)
|
||||
< end_idx
|
||||
):
|
||||
|
@ -250,16 +250,16 @@ class TraceFlow(object):
|
|||
for input_node in inputs:
|
||||
input_dict = {}
|
||||
input_node_idx = find_idx_by_name(
|
||||
input_node.name, self.trace_index.node_list
|
||||
input_node.name, self.trace_indice.node_list
|
||||
)
|
||||
for user in input_node.users.keys():
|
||||
if is_non_compute_node(user):
|
||||
continue
|
||||
user_idx = find_idx_by_name(user.name, self.trace_index.node_list)
|
||||
user_idx = find_idx_by_name(user.name, self.trace_indice.node_list)
|
||||
if start_idx <= user_idx <= end_idx:
|
||||
chunk_dim = all_node_info[user]["chunk_dim"]
|
||||
if chunk_dim is not None:
|
||||
user_source = self.trace_index._find_source_trace_from_node(
|
||||
user_source = self.trace_indice._find_source_trace_from_node(
|
||||
user
|
||||
)[chunk_dim]
|
||||
if input_node_idx in user_source:
|
||||
|
@ -282,7 +282,7 @@ class TraceFlow(object):
|
|||
if node_info["chunk_dim"] is None:
|
||||
maybe_prepose_nodes.append(node)
|
||||
maybe_prepose_nodes.sort(
|
||||
key=lambda x: find_idx_by_name(x.name, self.trace_index.node_list),
|
||||
key=lambda x: find_idx_by_name(x.name, self.trace_indice.node_list),
|
||||
reverse=True,
|
||||
) # from last node to first node
|
||||
prepose_nodes = []
|
||||
|
@ -308,7 +308,7 @@ class TraceFlow(object):
|
|||
if not (
|
||||
start_idx
|
||||
<= find_idx_by_name(
|
||||
cur_prepose_node_arg.name, self.trace_index.node_list
|
||||
cur_prepose_node_arg.name, self.trace_indice.node_list
|
||||
)
|
||||
< end_idx
|
||||
):
|
||||
|
@ -336,14 +336,14 @@ class TraceFlow(object):
|
|||
maybe_prepose_nodes.remove(n)
|
||||
# sort by index
|
||||
prepose_nodes.sort(
|
||||
key=lambda x: find_idx_by_name(x.name, self.trace_index.node_list)
|
||||
key=lambda x: find_idx_by_name(x.name, self.trace_indice.node_list)
|
||||
)
|
||||
|
||||
return prepose_nodes
|
||||
|
||||
def _get_non_chunk_inputs(self, chunk_info, start_idx, end_idx):
|
||||
# we need to log input nodes to avoid deleteing them in the loop
|
||||
chunk_node_list = self.trace_index.node_list[start_idx : end_idx + 1]
|
||||
chunk_node_list = self.trace_indice.node_list[start_idx : end_idx + 1]
|
||||
# also need to get some prepose node's arg out of non_chunk_inputs
|
||||
for n in chunk_info["args"]["prepose_nodes"]:
|
||||
chunk_node_list.remove(n)
|
||||
|
@ -355,7 +355,7 @@ class TraceFlow(object):
|
|||
|
||||
def flow_search(self, start_idx, start_dim, end_idx, end_dim):
|
||||
inputs, outputs = find_chunk_compute_input_and_output_nodes(
|
||||
self.trace_index.node_list[start_idx : end_idx + 1]
|
||||
self.trace_indice.node_list[start_idx : end_idx + 1]
|
||||
)
|
||||
# only single ouput
|
||||
if len(outputs) > 1:
|
||||
|
@ -403,10 +403,10 @@ class TraceFlow(object):
|
|||
chunk_shape = get_node_shape(chunk_info["outputs"][0])[
|
||||
chunk_info["outputs_dim"]
|
||||
]
|
||||
for node in self.trace_index.node_list[chunk_region[0] : chunk_region[1] + 1]:
|
||||
for node in self.trace_indice.node_list[chunk_region[0] : chunk_region[1] + 1]:
|
||||
if any(i in node.name for i in ["reshape", "view"]):
|
||||
reshape_args = node.args[1:]
|
||||
reshape_log = self.trace_index.idx_view_list[node]
|
||||
reshape_log = self.trace_indice.idx_view_list[node]
|
||||
chunk_dim = chunk_info["node_chunk_dim"][node]["chunk_dim"]
|
||||
reshape_size[node.name] = {}
|
||||
for reshape_arg_dim, reshape_arg in enumerate(reshape_args):
|
||||
|
|
|
@ -6,7 +6,7 @@ from .utils import (
|
|||
)
|
||||
|
||||
|
||||
class TraceIndex(object):
|
||||
class TraceIndice(object):
|
||||
def __init__(self, node_list) -> None:
|
||||
self.node_list = node_list
|
||||
self.idx_trace_list = self._init_idx_trace_list()
|
Loading…
Reference in New Issue