8000 17 update api by frankwhzhang · Pull Request #4294 · PaddlePaddle/models · GitHub
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17 update api #4294

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Merged
merged 2 commits into from
Feb 17, 2020
Merged

17 update api #4294

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74e193a
update1.7 save/load & fluid.data
frankwhzhang Feb 14, 2020
79474c1
update datafeed to dataloader
frankwhzhang Feb 17, 2020
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3 changes: 1 addition & 2 deletions PaddleRec/gru4rec/infer_sample_neg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,8 +47,7 @@ def infer(args, vocab_size, test_reader, use_cuda):
for epoch in range(start_index, last_index + 1):
copy_program = main_program.clone()
model_path = model_dir + "/epoch_" + str(epoch)
fluid.io.load_params(
executor=exe, dirname=model_path, main_program=copy_program)
fluid.load(copy_program, model_path, exe)
accum_num_recall = 0.0
accum_num_sum = 0.0
t0 = time.time()
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2 changes: 1 addition & 1 deletion PaddleRec/gru4rec/train_sample_neg.py
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Expand Up @@ -121,7 +121,7 @@ def train():
print("epoch:%d num_steps:%d time_cost(s):%f" %
(epoch_idx, i, total_time / epoch_idx))
save_dir = "%s/epoch_%d" % (model_dir, epoch_idx)
fluid.io.save_params(executor=exe, dirname=save_dir)
fluid.save(fluid.default_main_program(), model_path=save_dir)
print("model saved in %s" % save_dir)

print("finish training")
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30 changes: 8 additions & 22 deletions PaddleRec/multi-task/MMoE/mmoe_train.py
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8000
Original file line number Diff line number Diff line change
Expand Up @@ -59,27 +59,14 @@ def mmoe_layer(inputs, expert_num=8, gate_num=3):


def model(dict_dim, emb_dim):
label_like = fluid.layers.data(
name="label_like",
shape=[-1, 1],
dtype="int64",
lod_level=0,
append_batch_size=False)
label_comment = fluid.layers.data(
name="label_comment",
shape=[-1, 1],
dtype="int64",
lod_level=0,
append_batch_size=False)
label_share = fluid.layers.data(
name="label_share",
shape=[-1, 1],
dtype="int64",
lod_level=0,
append_batch_size=False)

a_data = fluid.layers.data(
name="a", shape=[-1, 1], dtype="int64", append_batch_size=False)
label_like = fluid.data(
name="label_like", shape=[-1, 1], dtype="int64", lod_level=0)
label_comment = fluid.data(
name="label_comment", shape=[-1, 1], dtype="int64", lod_level=0)
label_share = fluid.data(
name="label_share", shape=[-1, 1], dtype="int64", lod_level=0)

a_data = fluid.data(name="a", shape=[-1, 1], dtype="int64")
emb = fluid.layers.embedding(input=a_data, size=[dict_dim, emb_dim])

outs = mmoe_layer(emb, expert_num=8, gate_num=3)
Expand Down Expand Up @@ -127,7 +114,6 @@ def model(dict_dim, emb_dim):
sgd = fluid.optimizer.SGD(learning_rate=args.base_lr)
sgd.minimize(loss)
place = fluid.CUDAPlace(0) if args.use_gpu else fluid.CPUPlace()
feeder = fluid.DataFeeder(feed_list=data_list, place=place)
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
for batch_id in range(100):
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8 changes: 5 additions & 3 deletions PaddleRec/multiview_simnet/train.py
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Expand Up @@ -136,17 +136,19 @@ def start_train(args):
startup_program = fluid.default_startup_program()
loop_program = fluid.default_main_program()

feeder = fluid.DataFeeder(feed_list=all_slots, place=place)
exe = fluid.Executor(place)
exe.run(startup_program)
loader = fluid.io.DataLoader.from_generator(
feed_list=all_slots, capacity=10000, iterable=True)
loader.set_sample_list_generator(train_reader, places=place)

total_time = 0
ce_info = []
for pass_id in range(args.epochs):
start_time = time.time()
for batch_id, data in enumerate(train_reader()):
for batch_id, data in enumerate(loader()):
loss_val, correct_val = exe.run(loop_program,
feed=feeder.feed(data),
feed=data,
fetch_list=[avg_cost, correct])
logger.info("TRAIN --> pass: {} batch_id: {} avg_cost: {}, acc: {}"
.format(pass_id, batch_id, loss_val,
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2 changes: 1 addition & 1 deletion PaddleRec/ssr/cluster_train.py
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Expand Up @@ -121,7 +121,7 @@ def train_loop(main_program, avg_cost, acc, train_input_data, place, args,
print("epoch:%d num_steps:%d time_cost(s):%f" %
(epoch_idx, i, total_time / epoch_idx))
save_dir = "%s/epoch_%d" % (args.model_dir, epoch_idx)
fluid.io.save_params(executor=exe, dirname=save_dir)
fluid.save(fluid.default_main_program(), save_dir)
print("model saved in %s" % save_dir)

# only for ce
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3 changes: 1 addition & 2 deletions PaddleRec/ssr/infer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -84,8 +84,7 @@ def infer(args, vocab_size, test_reader):
for epoch in range(start_index, last_index + 1):
copy_program = main_program.clone()
model_path = model_dir + "/epoch_" + str(epoch)
fluid.io.load_params(
executor=exe, dirname=model_path, main_program=copy_program)
fluid.load(copy_program, model_path, exe)
accum_num_recall = 0.0
accum_num_sum = 0.0
t0 = time.time()
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11 changes: 7 additions & 4 deletions PaddleRec/ssr/train.py
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Expand Up @@ -87,9 +87,12 @@ def train(args):
optimizer.minimize(avg_cost)

data_list = [var.name for var in train_input_data]
feeder = fluid.DataFeeder(feed_list=data_list, place=place)
print(data_list)
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
loader = fluid.io.DataLoader.from_generator(
feed_list=train_input_data, capacity=10000, iterable=True)
loader.set_sample_list_generator(train_reader, places=place)
if parallel:
train_exe = fluid.ParallelExecutor(
use_cuda=use_cuda, loss_name=avg_cost.name)
Expand All @@ -103,10 +106,10 @@ def train(args):
print("epoch_%d start" % epoch_idx)
t0 = time.time()
i = 0
for batch_id, data in enumerate(train_reader()):
for batch_id, data in enumerate(loader()):
i += 1
loss_val, correct_val = train_exe.run(
feed=feeder.feed(data), fetch_list=[avg_cost.name, acc.name])
feed=data, fetch_list=[avg_cost.name, acc.name])
ce_info.append(float(np.mean(correct_val)) / args.batch_size)
if i % args.print_batch == 0:
logger.info(
Expand All @@ -121,7 +124,7 @@ def train(args):
print("epoch:%d num_steps:%d time_cost(s):%f" %
(epoch_idx, i, total_time / epoch_idx))
save_dir = "%s/epoch_%d" % (args.model_dir, epoch_idx)
fluid.io.save_params(executor=exe, dirname=save_dir)
fluid.save(fluid.default_main_program(), model_path=save_dir)
print("model saved in %s" % save_dir)

# only for ce
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