Spaces:
Running
Running
File size: 10,111 Bytes
a49be3b 06107a3 a49be3b 06107a3 a49be3b 06107a3 a49be3b 06107a3 a49be3b 06107a3 a49be3b 06107a3 a49be3b 06107a3 a49be3b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 |
from collections import defaultdict
from src.execution_model import Schedule, ScheduleConfig
def generate_1f1b_schedule(config: ScheduleConfig):
schedule = Schedule(config)
assert config.num_devices == config.num_stages, "num_devices must be equal to num_stages for 1F1B"
for i in range(config.num_devices):
fwd_batch_id = 0
bwd_batch_id = 0
cooldown_batches = warmup_batches = config.num_devices - i - 1
steady_batches = config.num_batches - warmup_batches
for _ in range(warmup_batches):
schedule.dev_queues[i].add_operation(
schedule.get_op(fwd_batch_id, i, "forward")
)
fwd_batch_id += 1
for _ in range(steady_batches):
schedule.dev_queues[i].add_operation(
schedule.get_op(fwd_batch_id, i, "forward")
)
fwd_batch_id += 1
schedule.dev_queues[i].add_operation(
schedule.get_op(bwd_batch_id, i, "backward")
)
bwd_batch_id += 1
for _ in range(cooldown_batches):
schedule.dev_queues[i].add_operation(
schedule.get_op(bwd_batch_id, i, "backward")
)
bwd_batch_id += 1
return schedule
def generate_zero_bubble_1p_schedule(config: ScheduleConfig):
# Create a new schedule with split_backward=True to support backward_D and backward_W operations
schedule = Schedule(config)
total_batches = config.num_batches
assert config.num_devices == config.num_stages, "num_devices must be equal to num_stages for ZB-1P"
for i in range(config.num_devices):
fwd_batch_id = 0
bwd_d_batch_id = 0
bwd_w_batch_id = 0
cooldown_batches = warmup_batches = config.num_devices - i - 1
steady_batches = total_batches - warmup_batches
for _ in range(warmup_batches):
schedule.dev_queues[i].add_operation(
schedule.get_op(fwd_batch_id, i, "forward")
)
fwd_batch_id += 1
for _ in range(steady_batches):
schedule.dev_queues[i].add_operation(
schedule.get_op(fwd_batch_id, i, "forward")
)
schedule.dev_queues[i].add_operation(
schedule.get_op(bwd_d_batch_id, i, "backward_D")
)
if fwd_batch_id - bwd_w_batch_id >= config.num_devices - 1:
schedule.dev_queues[i].add_operation(
schedule.get_op(bwd_w_batch_id, i, "backward_W")
)
bwd_w_batch_id += 1
bwd_d_batch_id += 1
fwd_batch_id += 1
for _ in range(cooldown_batches):
schedule.dev_queues[i].add_operation(
schedule.get_op(bwd_d_batch_id, i, "backward_D")
)
schedule.dev_queues[i].add_operation(
schedule.get_op(bwd_w_batch_id, i, "backward_W")
)
bwd_w_batch_id += 1
bwd_d_batch_id += 1
while bwd_w_batch_id < total_batches:
schedule.dev_queues[i].add_operation(
schedule.get_op(bwd_w_batch_id, i, "backward_W")
)
bwd_w_batch_id += 1
return schedule
# Some codes are copied from Megatron-LM
def generate_1f1b_interleave_schedule(config: ScheduleConfig):
schedule = Schedule(config)
def get_pp_rank_microbatches(
num_microbatches,
num_devices,
device_id,
num_stages_per_device,
microbatch_group_size_per_vp_stage,
):
"""Get the number of total, warmup, and remaining microbatches in PP scheduling."""
total_num_microbatches = num_microbatches * num_stages_per_device
are_all_microbatches_in_warmup = False
if num_devices > 1:
if num_stages_per_device is None:
# forward_backward_pipelining_without_interleaving
num_warmup_microbatches = num_devices - device_id - 1
else:
# forward_backward_pipelining_with_interleaving
# Run (num_model_chunks-1)*microbatch_group_size_per_vp_stage on
# all workers, followed by more microbatches after depending on
# stage ID (more forward passes for earlier stages, later stages can
# immediately start with 1F1B).
num_warmup_microbatches = (num_devices - device_id - 1) * 2
num_warmup_microbatches += (num_stages_per_device - 1) * microbatch_group_size_per_vp_stage
else:
# forward_backward_no_pipelining
num_warmup_microbatches = 1
if num_warmup_microbatches >= total_num_microbatches:
num_warmup_microbatches = total_num_microbatches
are_all_microbatches_in_warmup = True
num_microbatches_remaining = total_num_microbatches - num_warmup_microbatches
return (
total_num_microbatches,
are_all_microbatches_in_warmup,
num_warmup_microbatches,
num_microbatches_remaining,
)
def get_schedule_table(num_microbatches, num_model_chunks, microbatch_group_size_per_vp_stage):
"""Get the schedule table for PP scheduling.
Create a tunable schedule lookup table.
The schedule lookup table uses the virtual_microbatch_id to find the corresponding microbatch_id and model_chunk_id.
For example, the tunable schedule table for PP2 N3M5 with VP2 is constructed as below:
virtual_microbatch_id | 0 1 2 3 4 5 6 7 8 9
microbatch_id | 0 1 2 0 1 2 3 4 3 4
model_chunk_id | 0 0 0 1 1 1 0 0 1 1
"""
schedule_table = []
for min_microbatch_id_in_group in range(
0, num_microbatches, microbatch_group_size_per_vp_stage
):
if min_microbatch_id_in_group + microbatch_group_size_per_vp_stage >= num_microbatches:
# Construct schedule for the last microbatch group
schedule_table.extend(
[
(microbatch_id, model_chunk_id)
for model_chunk_id in range(num_model_chunks)
for microbatch_id in range(min_microbatch_id_in_group, num_microbatches)
]
)
else:
# Construct schedule for other microbatch groups
schedule_table.extend(
[
(microbatch_id, model_chunk_id)
for model_chunk_id in range(num_model_chunks)
for microbatch_id in range(
min_microbatch_id_in_group,
min_microbatch_id_in_group + microbatch_group_size_per_vp_stage,
)
]
)
return schedule_table
def convert_schedule_table_to_order(num_warmup_microbatches, num_model_chunks, schedule_table):
"""Convert a tunable schedule lookup table to the te.make_graphed_callables() accepted
order format. For example, the tunable schedule table for PP2 N3M5 with VP2 is as below:
virtual_microbatch_id | 0 1 2 3 4 5 6 7 8 9
microbatch_id | 0 1 2 0 1 2 3 4 3 4
model_chunk_id | 0 0 0 1 1 1 0 0 1 1
Then the forward backward separated order is:
forward | 1 1 1 2 2 2 1 1 2 2
backward | -2 -2 -2 -1 -1 -1 -2 -2 -1 -1
If num_warmup_microbatches is 5, the output order is:
1 1 1 2 2 2 -2 1 -2 1 -2 2 -1 2 -1 -1 -2 -2 -1 -1
"""
_, model_chunk_id_table = zip(*schedule_table)
forward_order = [chunk_id + 1 for chunk_id in model_chunk_id_table]
backward_order = [chunk_id - num_model_chunks for chunk_id in model_chunk_id_table]
order = forward_order[:num_warmup_microbatches]
for i in range(num_warmup_microbatches, len(forward_order)):
order.append(forward_order[i])
order.append(backward_order[i - num_warmup_microbatches])
if num_warmup_microbatches > 0:
order.extend(backward_order[-num_warmup_microbatches:])
return order
for device_id in range(config.num_devices):
microbatch_group_size_per_vp_stage = config.num_devices
total_num_microbatches, are_all_microbatches_in_warmup, num_warmup_microbatches, num_microbatches_remaining = get_pp_rank_microbatches(
config.num_batches,
config.num_devices,
device_id,
config.num_stages_per_device,
microbatch_group_size_per_vp_stage,
)
schedule_table = get_schedule_table(
config.num_batches,
config.num_stages_per_device,
microbatch_group_size_per_vp_stage,
)
order = convert_schedule_table_to_order(
num_warmup_microbatches,
num_model_chunks=config.num_stages_per_device,
schedule_table=schedule_table,
)
cur_stage_microbatch_id = {}
for i in range(1, config.num_stages_per_device+1):
cur_stage_microbatch_id[i] = 0
cur_stage_microbatch_id[-i] = 0
for order_item in order:
stage_id = schedule.dev_queues[device_id].stages[abs(order_item)-1]
if order_item > 0:
op_type = "forward"
micro_batch_id = cur_stage_microbatch_id[order_item]
cur_stage_microbatch_id[order_item] = cur_stage_microbatch_id[order_item] + 1
elif order_item < 0:
op_type = "backward"
micro_batch_id = cur_stage_microbatch_id[order_item]
cur_stage_microbatch_id[order_item] = cur_stage_microbatch_id[order_item] + 1
else:
raise ValueError(f"Invalid order item: {order_item}")
schedule.dev_queues[device_id].add_operation(
schedule.get_op(micro_batch_id, stage_id, op_type)
)
return schedule
|