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2022-06-05
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@yangguohao
yangguohao committed Jun 5, 2022
1 parent a6c17b0 commit 8b00df1
Showing 1 changed file with 161 additions and 120 deletions.
281 changes: 161 additions & 120 deletions python/paddle/fluid/tests/unittests/test_triplet_margin_with_distance_loss.py
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Expand Up @@ -17,30 +17,34 @@
import unittest


def call_TripletMarginDistanceLoss_layer(input,
positive,
negative,
distance_function=None,
margin=0.3,
swap=False,
reduction='mean',):
triplet_margin_with_distance_loss = paddle.nn.TripletMarginWithDistanceLoss(distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
res = triplet_margin_with_distance_loss(input=input,
positive=positive,
negative=negative,)
def call_TripletMarginDistanceLoss_layer(
input,
positive,
negative,
distance_function=None,
margin=0.3,
swap=False,
reduction='mean', ):
triplet_margin_with_distance_loss = paddle.nn.TripletMarginWithDistanceLoss(
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
res = triplet_margin_with_distance_loss(
input=input,
positive=positive,
negative=negative, )
return res


def call_TripletMaginDistanceLoss_functional(input,
positive,
negative,
distance_function = None,
margin=0.3,
swap=False,
reduction='mean',):
def call_TripletMaginDistanceLoss_functional(
input,
positive,
negative,
distance_function=None,
margin=0.3,
swap=False,
reduction='mean', ):
res = paddle.nn.functional.triplet_margin_with_distance_loss(
input=input,
positive=positive,
Expand Down Expand Up @@ -70,30 +74,37 @@ def test_static(place,
name='positive', shape=positive_np.shape, dtype='float64')
negative = paddle.static.data(
name='negative', shape=negative_np.shape, dtype='float64')
feed_dict = {"input": input_np, "positive": positive_np, "negative": negative_np}
feed_dict = {
"input": input_np,
"positive": positive_np,
"negative": negative_np
}

if functional:
res = call_TripletMaginDistanceLoss_functional(input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
res = call_TripletMaginDistanceLoss_functional(
input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
else:
res = call_TripletMarginDistanceLoss_layer(input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
res = call_TripletMarginDistanceLoss_layer(
input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)

exe = paddle.static.Executor(place)
static_result = exe.run(prog, feed=feed_dict, fetch_list=[res])

return static_result


def test_dygraph(place,
input,
positive,
Expand All @@ -109,33 +120,36 @@ def test_dygraph(place,
negative = paddle.to_tensor(negative)

if functional:
dy_res = call_TripletMaginDistanceLoss_functional(input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
dy_res = call_TripletMaginDistanceLoss_functional(
input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
else:
dy_res = call_TripletMarginDistanceLoss_layer(input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
dy_res = call_TripletMarginDistanceLoss_layer(
input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
margin=margin,
swap=swap,
reduction=reduction)
dy_result = dy_res.numpy()
paddle.enable_static()
return dy_result


def calc_triplet_margin_distance_loss(input,
positive,
negative,
distance_function=None,
margin=0.3,
swap=False,
reduction='mean',):
def calc_triplet_margin_distance_loss(
input,
positive,
negative,
distance_function=None,
margin=0.3,
swap=False,
reduction='mean', ):
distance_function = np.linalg.norm
positive_dist = distance_function((input - positive), 2, axis=1)
negative_dist = distance_function((input - negative), 2, axis=1)
Expand Down Expand Up @@ -167,31 +181,35 @@ def test_TripletMarginDistanceLoss(self):
reductions = ['sum', 'mean', 'none']
for place in places:
for reduction in reductions:
expected = calc_triplet_margin_distance_loss(input=input,
positive=positive,
negative=negative,
reduction=reduction)

dy_result = test_dygraph(place=place,
input=input,
positive=positive,
negative=negative,
reduction=reduction,)

static_result = test_static(place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
reduction=reduction,)
expected = calc_triplet_margin_distance_loss(
input=input,
positive=positive,
negative=negative,
reduction=reduction)

dy_result = test_dygraph(
place=place,
input=input,
positive=positive,
negative=negative,
reduction=reduction, )

static_result = test_static(
place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
reduction=reduction, )
self.assertTrue(np.allclose(static_result, expected))
self.assertTrue(np.allclose(static_result, dy_result))
self.assertTrue(np.allclose(dy_result, expected))
static_functional = test_static(place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
reduction=reduction,
functional=True)
static_functional = test_static(
place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
reduction=reduction,
functional=True)
dy_functional = test_dygraph(
place=place,
input=input,
Expand Down Expand Up @@ -222,42 +240,44 @@ def test_TripletMarginDistanceLoss_error(self):
paddle.enable_static()

def test_TripletMarginDistanceLoss_distance_function(self):

def distance_function_1(x1, x2):
return 1.0 - paddle.nn.functional.cosine_similarity(x1, x2)

def distance_function_2(x1, x2):
return paddle.max(paddle.abs(x1-x2), axis=1)
return paddle.max(paddle.abs(x1 - x2), axis=1)

distance_function_list = [distance_function_1,distance_function_2]
distance_function_list = [distance_function_1, distance_function_2]
input = np.random.uniform(0.1, 0.8, size=(20, 30)).astype(np.float64)
positive = np.random.uniform(0, 2, size=(20, 30)).astype(np.float64)
negative = np.random.uniform(0, 2, size=(20, 30)).astype(np.float64)

place = paddle.CPUPlace()
reduction = 'mean'
for distance_function in distance_function_list:
dy_result = test_dygraph(place=place,
input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
reduction=reduction,)

static_result = test_static(place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
distance_function=distance_function,
reduction=reduction,)
dy_result = test_dygraph(
place=place,
input=input,
positive=positive,
negative=negative,
distance_function=distance_function,
reduction=reduction, )

static_result = test_static(
place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
distance_function=distance_function,
reduction=reduction, )
self.assertTrue(np.allclose(static_result, dy_result))
static_functional = test_static(place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
distance_function=distance_function,
reduction=reduction,
functional=True)
static_functional = test_static(
place=place,
input_np=input,
positive_np=positive,
negative_np=negative,
distance_function=distance_function,
reduction=reduction,
functional=True)
dy_functional = test_dygraph(
place=place,
input=input,
Expand All @@ -271,8 +291,9 @@ def distance_function_2(x1, x2):
def test_TripletMarginWithDistanceLoss_distance_funtion_error(self):
paddle.disable_static()

def distance_function(x1,x2):
def distance_function(x1, x2):
return -1.0 - paddle.nn.functional.cosine_similarity(x1, x2)

func = distance_function
input = np.random.uniform(0.1, 0.8, size=(20, 30)).astype(np.float64)
positive = np.random.uniform(0, 2, size=(20, 30)).astype(np.float64)
Expand All @@ -284,7 +305,7 @@ def distance_function(x1,x2):
input=input,
positive=positive,
negative=negative,
distance_function=func,)
distance_function=func, )
paddle.enable_static()

def test_TripletMarginDistanceLoss_dimension(self):
Expand All @@ -299,7 +320,8 @@ def test_TripletMarginDistanceLoss_dimension(self):
input=input,
positive=positive,
negative=negative, )
triplet_margin_with_distance_loss = paddle.nn.loss.TripletMarginWithDistanceLoss()
triplet_margin_with_distance_loss = paddle.nn.loss.TripletMarginWithDistanceLoss(
)
self.assertRaises(
ValueError,
triplet_margin_with_distance_loss,
Expand All @@ -314,26 +336,45 @@ def test_TripletMarginWithDistanceLoss_swap(self):
input = np.random.uniform(0.1, 0.8, size=(20, 30)).astype(np.float64)
positive = np.random.uniform(0, 2, size=(20, 30)).astype(np.float64)
negative = np.random.uniform(0, 2, size=(20, 30)).astype(np.float64)
expected = calc_triplet_margin_distance_loss(input=input, swap=True, positive=positive, negative=negative,
reduction=reduction)

dy_result = test_dygraph(place=place, swap=True,
input=input, positive=positive, negative=negative,
reduction=reduction, )
expected = calc_triplet_margin_distance_loss(
input=input,
swap=True,
positive=positive,
negative=negative,
reduction=reduction)

static_result = test_static(place=place, swap=True,
input_np=input, positive_np=positive, negative_np=negative,
reduction=reduction, )
dy_result = test_dygraph(
place=place,
swap=True,
input=input,
positive=positive,
negative=negative,
reduction=reduction, )

static_result = test_static(
place=place,
swap=True,
input_np=input,
positive_np=positive,
negative_np=negative,
reduction=reduction, )
self.assertTrue(np.allclose(static_result, expected))
self.assertTrue(np.allclose(static_result, dy_result))
self.assertTrue(np.allclose(dy_result, expected))
static_functional = test_static(place=place, swap=True,
input_np=input, positive_np=positive, negative_np=negative,
reduction=reduction,
functional=True)
static_functional = test_static(
place=place,
swap=True,
input_np=input,
positive_np=positive,
negative_np=negative,
reduction=reduction,
functional=True)
dy_functional = test_dygraph(
place=place, swap=True,
input=input, positive=positive, negative=negative,
place=place,
swap=True,
input=input,
positive=positive,
negative=negative,
reduction=reduction,
functional=True)
self.assertTrue(np.allclose(static_functional, expected))
Expand Down

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