fix tps and fix trt

This commit is contained in:
LDOUBLEV 2021-06-09 19:15:57 +08:00
parent 796898e0f8
commit 616ad6a179
2 changed files with 9 additions and 36 deletions

View File

@ -230,15 +230,10 @@ class GridGenerator(nn.Layer):
def build_inv_delta_C_paddle(self, C):
""" Return inv_delta_C which is needed to calculate T """
F = self.F
hat_C = paddle.zeros((F, F), dtype='float64') # F x F
for i in range(0, F):
for j in range(i, F):
if i == j:
hat_C[i, j] = 1
else:
r = paddle.norm(C[i] - C[j])
hat_C[i, j] = r
hat_C[j, i] = r
hat_eye = paddle.eye(F, dtype='float64') # F x F
tmp1 = C.reshape([1, F, 2])
tmp2 = C.reshape([F, 1, 2])
hat_C = paddle.norm(tmp1 - tmp2, axis=2) + hat_eye
hat_C = (hat_C**2) * paddle.log(hat_C)
delta_C = paddle.concat( # F+3 x F+3
[

View File

@ -235,12 +235,13 @@ def create_predictor(args, mode, logger):
config.enable_tensorrt_engine(
precision_mode=inference.PrecisionType.Float32,
max_batch_size=args.max_batch_size,
min_subgraph_size=10) # skip the minmum trt subgraph
if mode == "det" and "mobile" in model_file_path:
min_subgraph_size=3) # skip the minmum trt subgraph
if mode == "det":
min_input_shape = {
"x": [1, 3, 50, 50],
"conv2d_92.tmp_0": [1, 96, 20, 20],
"conv2d_91.tmp_0": [1, 96, 10, 10],
"conv2d_59.tmp_0": [1, 96, 20, 20],
"nearest_interp_v2_1.tmp_0": [1, 96, 10, 10],
"nearest_interp_v2_2.tmp_0": [1, 96, 20, 20],
"nearest_interp_v2_3.tmp_0": [1, 24, 20, 20],
@ -253,6 +254,7 @@ def create_predictor(args, mode, logger):
"x": [1, 3, 2000, 2000],
"conv2d_92.tmp_0": [1, 96, 400, 400],
"conv2d_91.tmp_0": [1, 96, 200, 200],
"conv2d_59.tmp_0": [1, 96, 400, 400],
"nearest_interp_v2_1.tmp_0": [1, 96, 200, 200],
"nearest_interp_v2_2.tmp_0": [1, 96, 400, 400],
"nearest_interp_v2_3.tmp_0": [1, 24, 400, 400],
@ -265,6 +267,7 @@ def create_predictor(args, mode, logger):
"x": [1, 3, 640, 640],
"conv2d_92.tmp_0": [1, 96, 160, 160],
"conv2d_91.tmp_0": [1, 96, 80, 80],
"conv2d_59.tmp_0": [1, 96, 160, 160],
"nearest_interp_v2_1.tmp_0": [1, 96, 80, 80],
"nearest_interp_v2_2.tmp_0": [1, 96, 160, 160],
"nearest_interp_v2_3.tmp_0": [1, 24, 160, 160],
@ -273,31 +276,6 @@ def create_predictor(args, mode, logger):
"elementwise_add_7": [1, 56, 40, 40],
"nearest_interp_v2_0.tmp_0": [1, 96, 40, 40]
}
if mode == "det" and "server" in model_file_path:
min_input_shape = {
"x": [1, 3, 50, 50],
"conv2d_59.tmp_0": [1, 96, 20, 20],
"nearest_interp_v2_2.tmp_0": [1, 96, 20, 20],
"nearest_interp_v2_3.tmp_0": [1, 24, 20, 20],
"nearest_interp_v2_4.tmp_0": [1, 24, 20, 20],
"nearest_interp_v2_5.tmp_0": [1, 24, 20, 20]
}
max_input_shape = {
"x": [1, 3, 2000, 2000],
"conv2d_59.tmp_0": [1, 96, 400, 400],
"nearest_interp_v2_2.tmp_0": [1, 96, 400, 400],
"nearest_interp_v2_3.tmp_0": [1, 24, 400, 400],
"nearest_interp_v2_4.tmp_0": [1, 24, 400, 400],
"nearest_interp_v2_5.tmp_0": [1, 24, 400, 400]
}
opt_input_shape = {
"x": [1, 3, 640, 640],
"conv2d_59.tmp_0": [1, 96, 160, 160],
"nearest_interp_v2_2.tmp_0": [1, 96, 160, 160],
"nearest_interp_v2_3.tmp_0": [1, 24, 160, 160],
"nearest_interp_v2_4.tmp_0": [1, 24, 160, 160],
"nearest_interp_v2_5.tmp_0": [1, 24, 160, 160]
}
elif mode == "rec":
min_input_shape = {"x": [args.rec_batch_num, 3, 32, 10]}
max_input_shape = {"x": [args.rec_batch_num, 3, 32, 2000]}