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提交 dfa731e1 编写于 作者: L liuruilong
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src/operators/kernel/arm/batchnorm_kernel.cpp
浏览文件 @ dfa731e1
...@@ -45,34 +45,35 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const { ...@@ -45,34 +45,35 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const {
auto scale_ptr = scale->data<float>(); auto scale_ptr = scale->data<float>();
auto bias_ptr = bias->data<float>(); auto bias_ptr = bias->data<float>();
// Tensor inv_std; // Tensor inv_std;
// auto inv_std_ptr = inv_std.mutable_data<float>(make_ddim({C})); // auto inv_std_ptr = inv_std.mutable_data<float>(make_ddim({C}));
PADDLE_MOBILE_ENFORCE(C == variance->numel(), "C must equal to variance.numel()"); PADDLE_MOBILE_ENFORCE(C == variance->numel(),
"C must equal to variance.numel()");
int HXW = H * W; int HXW = H * W;
if (HXW > 32) { if (HXW > 32) {
int NXC = N * C; int NXC = N * C;
float *inv_std_ptr = new float[NXC * 4]; float *inv_std_ptr = new float[NXC * 4];
float * volatile new_scale_ptr = new float[NXC * 4]; float *volatile new_scale_ptr = new float[NXC * 4];
float * volatile new_bias_ptr = new float[NXC * 4]; float *volatile new_bias_ptr = new float[NXC * 4];
/// std = (var + epsilon).sqrt(); /// std = (var + epsilon).sqrt();
/// inv_std = 1 / std; /// inv_std = 1 / std;
for (int i = 0; i < C * 4; i += 4) { for (int i = 0; i < C * 4; i += 4) {
inv_std_ptr[i] = inv_std_ptr[i] =
1 / static_cast<float>(pow((variance_ptr[i/4] + epsilon), 0.5)); 1 / static_cast<float>(pow((variance_ptr[i / 4] + epsilon), 0.5));
inv_std_ptr[i + 1] = inv_std_ptr[i]; inv_std_ptr[i + 1] = inv_std_ptr[i];
inv_std_ptr[i + 2] = inv_std_ptr[i]; inv_std_ptr[i + 2] = inv_std_ptr[i];
inv_std_ptr[i + 3] = inv_std_ptr[i]; inv_std_ptr[i + 3] = inv_std_ptr[i];
new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i/4]; new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i / 4];
new_scale_ptr[i + 1] = new_scale_ptr[i]; new_scale_ptr[i + 1] = new_scale_ptr[i];
new_scale_ptr[i + 2] = new_scale_ptr[i]; new_scale_ptr[i + 2] = new_scale_ptr[i];
new_scale_ptr[i + 3] = new_scale_ptr[i]; new_scale_ptr[i + 3] = new_scale_ptr[i];
new_bias_ptr[i] = bias_ptr[i/4] - mean_ptr[i/4] * inv_std_ptr[i] * scale_ptr[i/4]; new_bias_ptr[i] =
bias_ptr[i / 4] - mean_ptr[i / 4] * inv_std_ptr[i] * scale_ptr[i / 4];
new_bias_ptr[i + 1] = new_bias_ptr[i]; new_bias_ptr[i + 1] = new_bias_ptr[i];
new_bias_ptr[i + 2] = new_bias_ptr[i]; new_bias_ptr[i + 2] = new_bias_ptr[i];
...@@ -84,116 +85,116 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const { ...@@ -84,116 +85,116 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const {
new_bias_ptr[j] = new_bias_ptr[j - C * 4]; new_bias_ptr[j] = new_bias_ptr[j - C * 4];
} }
asm volatile( asm volatile(
"subs %[N], %[N], #1 \n\t" "subs %[N], %[N], #1 \n\t"
"blt end_n_%= \n\t" "blt end_n_%= \n\t"
"loop_n_%=: \n\t" "loop_n_%=: \n\t"
"subs %[C], %[C], #1 \n\t" "subs %[C], %[C], #1 \n\t"
"blt end_c_%= \n\t" "blt end_c_%= \n\t"
"loop_c_%=: \n\t" "loop_c_%=: \n\t"
"vld1.32 {q9}, [%[new_scale_ptr]]! \n\t" "vld1.32 {q9}, [%[new_scale_ptr]]! \n\t"
"vld1.32 {q10}, [%[new_bias_ptr]]! \n\t" "vld1.32 {q10}, [%[new_bias_ptr]]! \n\t"
"mov r6, %[HXW] \n\t" "mov r6, %[HXW] \n\t"
"subs r6, r6, #32 \n\t" "subs r6, r6, #32 \n\t"
"blt end_hw_%= \n\t" "blt end_hw_%= \n\t"
"loop_hw_%=: \n\t" "loop_hw_%=: \n\t"
"vld1.32 {q1, q2}, [%[input_x_ptr]]! \n\t" "vld1.32 {q1, q2}, [%[input_x_ptr]]! \n\t"
"vld1.32 {q3, q4}, [%[input_x_ptr]]! \n\t" "vld1.32 {q3, q4}, [%[input_x_ptr]]! \n\t"
"vld1.32 {q5, q6}, [%[input_x_ptr]]! \n\t" "vld1.32 {q5, q6}, [%[input_x_ptr]]! \n\t"
"vld1.32 {q7, q8}, [%[input_x_ptr]]! \n\t" "vld1.32 {q7, q8}, [%[input_x_ptr]]! \n\t"
"vmul.f32 q1, q1, q9 \n\t" "vmul.f32 q1, q1, q9 \n\t"
"vmul.f32 q2, q2, q9 \n\t" "vmul.f32 q2, q2, q9 \n\t"
"vmul.f32 q3, q3, q9 \n\t" "vmul.f32 q3, q3, q9 \n\t"
"vmul.f32 q4, q4, q9 \n\t" "vmul.f32 q4, q4, q9 \n\t"
"vmul.f32 q5, q5, q9 \n\t" "vmul.f32 q5, q5, q9 \n\t"
"vmul.f32 q6, q6, q9 \n\t" "vmul.f32 q6, q6, q9 \n\t"
"vmul.f32 q7, q7, q9 \n\t" "vmul.f32 q7, q7, q9 \n\t"
"vmul.f32 q8, q8, q9 \n\t" "vmul.f32 q8, q8, q9 \n\t"
"vadd.f32 q1, q1, q10 \n\t" "vadd.f32 q1, q1, q10 \n\t"
"vadd.f32 q2, q2, q10 \n\t" "vadd.f32 q2, q2, q10 \n\t"
"vadd.f32 q3, q3, q10 \n\t" "vadd.f32 q3, q3, q10 \n\t"
"vadd.f32 q4, q4, q10 \n\t" "vadd.f32 q4, q4, q10 \n\t"
"vadd.f32 q5, q5, q10 \n\t" "vadd.f32 q5, q5, q10 \n\t"
"vadd.f32 q6, q6, q10 \n\t" "vadd.f32 q6, q6, q10 \n\t"
"vadd.f32 q7, q7, q10 \n\t" "vadd.f32 q7, q7, q10 \n\t"
"vadd.f32 q8, q8, q10 \n\t" "vadd.f32 q8, q8, q10 \n\t"
"vst1.32 {q1, q2}, [%[out_ptr]]! \n\t" "vst1.32 {q1, q2}, [%[out_ptr]]! \n\t"
"vst1.32 {q3, q4}, [%[out_ptr]]! \n\t" "vst1.32 {q3, q4}, [%[out_ptr]]! \n\t"
"vst1.32 {q5, q6}, [%[out_ptr]]! \n\t" "vst1.32 {q5, q6}, [%[out_ptr]]! \n\t"
"vst1.32 {q7, q8}, [%[out_ptr]]! \n\t" "vst1.32 {q7, q8}, [%[out_ptr]]! \n\t"
"subs r6, r6, #32 \n\t" "subs r6, r6, #32 \n\t"
"bge loop_hw_%= \n\t" "bge loop_hw_%= \n\t"
"end_hw_%=: \n\t" "end_hw_%=: \n\t"
"cmp r6, #0 \n\t" "cmp r6, #0 \n\t"
"bge end_remainder_%= \n\t" "bge end_remainder_%= \n\t"
"mov r5, #4 \n\t" "mov r5, #4 \n\t"
"mul r6, r6, r5 \n\t" "mul r6, r6, r5 \n\t"
"add %[input_x_ptr], %[input_x_ptr], r6 \n\t" "add %[input_x_ptr], %[input_x_ptr], r6 \n\t"
"vld1.32 {q1, q2}, [%[input_x_ptr]]! \n\t" "vld1.32 {q1, q2}, [%[input_x_ptr]]! \n\t"
"vld1.32 {q3, q4}, [%[input_x_ptr]]! \n\t" "vld1.32 {q3, q4}, [%[input_x_ptr]]! \n\t"
"vld1.32 {q5, q6}, [%[input_x_ptr]]! \n\t" "vld1.32 {q5, q6}, [%[input_x_ptr]]! \n\t"
"vld1.32 {q7, q8}, [%[input_x_ptr]]! \n\t" "vld1.32 {q7, q8}, [%[input_x_ptr]]! \n\t"
"vmul.f32 q1, q1, q9 \n\t" "vmul.f32 q1, q1, q9 \n\t"
"vmul.f32 q2, q2, q9 \n\t" "vmul.f32 q2, q2, q9 \n\t"
"vmul.f32 q3, q3, q9 \n\t" "vmul.f32 q3, q3, q9 \n\t"
"vmul.f32 q4, q4, q9 \n\t" "vmul.f32 q4, q4, q9 \n\t"
"vmul.f32 q5, q5, q9 \n\t" "vmul.f32 q5, q5, q9 \n\t"
"vmul.f32 q6, q6, q9 \n\t" "vmul.f32 q6, q6, q9 \n\t"
"vmul.f32 q7, q7, q9 \n\t" "vmul.f32 q7, q7, q9 \n\t"
"vmul.f32 q8, q8, q9 \n\t" "vmul.f32 q8, q8, q9 \n\t"
"vadd.f32 q1, q1, q10 \n\t" "vadd.f32 q1, q1, q10 \n\t"
"vadd.f32 q2, q2, q10 \n\t" "vadd.f32 q2, q2, q10 \n\t"
"vadd.f32 q3, q3, q10 \n\t" "vadd.f32 q3, q3, q10 \n\t"
"vadd.f32 q4, q4, q10 \n\t" "vadd.f32 q4, q4, q10 \n\t"
"vadd.f32 q5, q5, q10 \n\t" "vadd.f32 q5, q5, q10 \n\t"
"vadd.f32 q6, q6, q10 \n\t" "vadd.f32 q6, q6, q10 \n\t"
"vadd.f32 q7, q7, q10 \n\t" "vadd.f32 q7, q7, q10 \n\t"
"vadd.f32 q8, q8, q10 \n\t" "vadd.f32 q8, q8, q10 \n\t"
"add %[out_ptr], %[out_ptr], r6 \n\t" "add %[out_ptr], %[out_ptr], r6 \n\t"
"vst1.32 {q1, q2}, [%[out_ptr]]! \n\t" "vst1.32 {q1, q2}, [%[out_ptr]]! \n\t"
"vst1.32 {q3, q4}, [%[out_ptr]]! \n\t" "vst1.32 {q3, q4}, [%[out_ptr]]! \n\t"
"vst1.32 {q5, q6}, [%[out_ptr]]! \n\t" "vst1.32 {q5, q6}, [%[out_ptr]]! \n\t"
"vst1.32 {q7, q8}, [%[out_ptr]]! \n\t" "vst1.32 {q7, q8}, [%[out_ptr]]! \n\t"
"end_remainder_%=: \n\t" "end_remainder_%=: \n\t"
"subs %[C], %[C], #1 \n\t" "subs %[C], %[C], #1 \n\t"
"bge loop_c_%= \n\t" "bge loop_c_%= \n\t"
"end_c_%=: \n\t" "end_c_%=: \n\t"
"subs %[N], %[N], #1 \n\t" "subs %[N], %[N], #1 \n\t"
"bge loop_n_%= \n\t" "bge loop_n_%= \n\t"
"end_n_%=: \n\t" "end_n_%=: \n\t"
: :
:[input_x_ptr]"r"(input_x_ptr), [out_ptr]"r"(out_ptr), [new_scale_ptr]"r"(new_scale_ptr), [new_bias_ptr]"r"(new_bias_ptr), : [input_x_ptr] "r"(input_x_ptr), [out_ptr] "r"(out_ptr),
[N]"r"(N), [C]"r"(C), [HXW]"r"(HXW) [new_scale_ptr] "r"(new_scale_ptr), [new_bias_ptr] "r"(new_bias_ptr),
:"memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9", "q10", "r5", "r6" [N] "r"(N), [C] "r"(C), [HXW] "r"(HXW)
); : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9",
"q10", "r5", "r6");
delete [] inv_std_ptr;
delete [] new_scale_ptr; delete[] inv_std_ptr;
delete [] new_bias_ptr; delete[] new_scale_ptr;
delete[] new_bias_ptr;
} else { } else {
float *inv_std_ptr = new float[C]; float *inv_std_ptr = new float[C];
for (int i = 0; i < C; i++) { for (int i = 0; i < C; i++) {
inv_std_ptr[i] = inv_std_ptr[i] =
1 / static_cast<float>(pow((variance_ptr[i] + epsilon), 0.5)); 1 / static_cast<float>(pow((variance_ptr[i] + epsilon), 0.5));
} }
Tensor new_scale; Tensor new_scale;
...@@ -205,7 +206,8 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const { ...@@ -205,7 +206,8 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const {
/// (x * inv_var * scale) + (bias - est_mean * inv_var * scale) /// (x * inv_var * scale) + (bias - est_mean * inv_var * scale)
for (int i = 0; i < C; i++) { for (int i = 0; i < C; i++) {
new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i]; new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i];
new_bias_ptr[i] = bias_ptr[i] - mean_ptr[i] * inv_std_ptr[i] * scale_ptr[i]; new_bias_ptr[i] =
bias_ptr[i] - mean_ptr[i] * inv_std_ptr[i] * scale_ptr[i];
{ {
for (int n = 0; n < N; n++) { for (int n = 0; n < N; n++) {
for (int h = 0; h < H; h++) { for (int h = 0; h < H; h++) {
...@@ -213,23 +215,22 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const { ...@@ -213,23 +215,22 @@ void BatchNormKernel<CPU, float>::Compute(const BatchNormParam &param) const {
for (int w = 0; w < W; w++) { for (int w = 0; w < W; w++) {
int index = tmp_index + w; int index = tmp_index + w;
out_ptr[index] = out_ptr[index] =
input_x_ptr[index] * new_scale_ptr[i] + new_bias_ptr[i]; input_x_ptr[index] * new_scale_ptr[i] + new_bias_ptr[i];
} }
} }
} }
} }
} }
delete [] inv_std_ptr; delete[] inv_std_ptr;
// DLOG << "input[2,5,1,0](input[102]) ,channel 5 :"; // DLOG << "input[2,5,1,0](input[102]) ,channel 5 :";
// DLOG << "input_x_ptr : " << input_x_ptr[102]; // DLOG << "input_x_ptr : " << input_x_ptr[102];
// DLOG << "variance : " << variance_ptr[5]; // DLOG << "variance : " << variance_ptr[5];
// DLOG << "inv_std_ptr : " << inv_std_ptr[5]; // DLOG << "inv_std_ptr : " << inv_std_ptr[5];
// DLOG << "new_scale_ptr : " << new_scale_ptr[5]; // DLOG << "new_scale_ptr : " << new_scale_ptr[5];
// DLOG << "new_bias_ptr : " << new_bias_ptr[5]; // DLOG << "new_bias_ptr : " << new_bias_ptr[5];
// DLOG << "out_ptr : " << out_ptr[102]; // DLOG << "out_ptr : " << out_ptr[102];
} }
} }
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
......
src/operators/kernel/arm/relu_kernel.cpp
浏览文件 @ dfa731e1
...@@ -38,70 +38,71 @@ void ReluKernel<CPU, float>::Compute(const ReluParam &param) const { ...@@ -38,70 +38,71 @@ void ReluKernel<CPU, float>::Compute(const ReluParam &param) const {
auto *out_ptr = out->mutable_data<float>(); auto *out_ptr = out->mutable_data<float>();
int numel = input_x->numel(); int numel = input_x->numel();
// if (numel > 64) { // if (numel > 64) {
// asm volatile( // asm volatile(
// "pld [%[input_x_ptr], #0] \n\t" // "pld [%[input_x_ptr], #0] \n\t"
// "vmov.f32 q8, #0.0 \n\t" // "vmov.f32 q8, #0.0 \n\t"
// "subs %[num], %[num], #32 \n\t" // "subs %[num], %[num], #32 \n\t"
// "blt end_num_%= \n\t" // "blt end_num_%= \n\t"
// "loop_num_%=: \n\t" // "loop_num_%=: \n\t"
// "pld [%[input_x_ptr], #1024] \n\t" // "pld [%[input_x_ptr], #1024] \n\t"
// //
// "vld1.32 {q0, q1}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q0, q1}, [%[input_x_ptr]]! \n\t"
// "vld1.32 {q2, q3}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q2, q3}, [%[input_x_ptr]]! \n\t"
// "vld1.32 {q4, q5}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q4, q5}, [%[input_x_ptr]]! \n\t"
// "vld1.32 {q6, q7}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q6, q7}, [%[input_x_ptr]]! \n\t"
// //
// "vmax.f32 q0, q0, q8 \n\t" // "vmax.f32 q0, q0, q8 \n\t"
// "vmax.f32 q1, q1, q8 \n\t" // "vmax.f32 q1, q1, q8 \n\t"
// "vmax.f32 q2, q2, q8 \n\t" // "vmax.f32 q2, q2, q8 \n\t"
// "vmax.f32 q3, q3, q8 \n\t" // "vmax.f32 q3, q3, q8 \n\t"
// "vmax.f32 q4, q4, q8 \n\t" // "vmax.f32 q4, q4, q8 \n\t"
// "vmax.f32 q5, q5, q8 \n\t" // "vmax.f32 q5, q5, q8 \n\t"
// "vmax.f32 q6, q6, q8 \n\t" // "vmax.f32 q6, q6, q8 \n\t"
// "vmax.f32 q7, q7, q8 \n\t" // "vmax.f32 q7, q7, q8 \n\t"
// //
// "vst1.32 {q0, q1}, [%[out_ptr]]! \n\t" // "vst1.32 {q0, q1}, [%[out_ptr]]! \n\t"
// "vst1.32 {q2, q3}, [%[out_ptr]]! \n\t" // "vst1.32 {q2, q3}, [%[out_ptr]]! \n\t"
// "vst1.32 {q4, q5}, [%[out_ptr]]! \n\t" // "vst1.32 {q4, q5}, [%[out_ptr]]! \n\t"
// "vst1.32 {q6, q7}, [%[out_ptr]]! \n\t" // "vst1.32 {q6, q7}, [%[out_ptr]]! \n\t"
// //
// "subs %[num], %[num], #32 \n\t" // "subs %[num], %[num], #32 \n\t"
// "bge loop_num_%= \n\t" // "bge loop_num_%= \n\t"
// "end_num_%=: \n\t" // "end_num_%=: \n\t"
// "cmp %[num], #0 \n\t" // "cmp %[num], #0 \n\t"
// "bge end_%= \n\t" // "bge end_%= \n\t"
// "mov r6, #4 \n\t" // "mov r6, #4 \n\t"
// "mul r5, %[num], r6 \n\t" // "mul r5, %[num], r6 \n\t"
// "add %[input_x_ptr], %[input_x_ptr], r5 \n\t" // "add %[input_x_ptr], %[input_x_ptr], r5 \n\t"
// "vld1.32 {q0, q1}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q0, q1}, [%[input_x_ptr]]! \n\t"
// "vld1.32 {q2, q3}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q2, q3}, [%[input_x_ptr]]! \n\t"
// "vld1.32 {q4, q5}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q4, q5}, [%[input_x_ptr]]! \n\t"
// "vld1.32 {q6, q7}, [%[input_x_ptr]]! \n\t" // "vld1.32 {q6, q7}, [%[input_x_ptr]]! \n\t"
// "vmax.f32 q0, q0, q8 \n\t" // "vmax.f32 q0, q0, q8 \n\t"
// "vmax.f32 q1, q1, q8 \n\t" // "vmax.f32 q1, q1, q8 \n\t"
// "vmax.f32 q2, q2, q8 \n\t" // "vmax.f32 q2, q2, q8 \n\t"
// "vmax.f32 q3, q3, q8 \n\t" // "vmax.f32 q3, q3, q8 \n\t"
// "vmax.f32 q4, q4, q8 \n\t" // "vmax.f32 q4, q4, q8 \n\t"
// "vmax.f32 q5, q5, q8 \n\t" // "vmax.f32 q5, q5, q8 \n\t"
// "vmax.f32 q6, q6, q8 \n\t" // "vmax.f32 q6, q6, q8 \n\t"
// "vmax.f32 q7, q7, q8 \n\t" // "vmax.f32 q7, q7, q8 \n\t"
// "add %[out_ptr], %[out_ptr], r5 \n\t" // "add %[out_ptr], %[out_ptr], r5 \n\t"
// "vst1.32 {q0, q1}, [%[out_ptr]]! \n\t" // "vst1.32 {q0, q1}, [%[out_ptr]]! \n\t"
// "vst1.32 {q2, q3}, [%[out_ptr]]! \n\t" // "vst1.32 {q2, q3}, [%[out_ptr]]! \n\t"
// "vst1.32 {q4, q5}, [%[out_ptr]]! \n\t" // "vst1.32 {q4, q5}, [%[out_ptr]]! \n\t"
// "vst1.32 {q6, q7}, [%[out_ptr]]! \n\t" // "vst1.32 {q6, q7}, [%[out_ptr]]! \n\t"
// "end_%=: \n\t" // "end_%=: \n\t"
// : // :
// : // :
// [out_ptr] "r"(out_ptr), [input_x_ptr] "r"(input_x_ptr), [num] "r"(numel) // [out_ptr] "r"(out_ptr), [input_x_ptr] "r"(input_x_ptr), [num]
// : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "r5", // "r"(numel) : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6",
// "r6"); // "q7", "q8", "r5",
// } else { // "r6");
ReluFunctor<float> func_; // } else {
math::Transform trans; ReluFunctor<float> func_;
trans(input_x_ptr, input_x_ptr + numel, out_ptr, func_); math::Transform trans;
// } trans(input_x_ptr, input_x_ptr + numel, out_ptr, func_);
// }
} }
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
......
test/common/test_lib_size.h
浏览文件 @ dfa731e1
...@@ -19,9 +19,9 @@ limitations under the License. */ ...@@ -19,9 +19,9 @@ limitations under the License. */
#ifndef PADDLE_MOBILE_TEST_LIB_SIZE_H #ifndef PADDLE_MOBILE_TEST_LIB_SIZE_H
#define PADDLE_MOBILE_TEST_LIB_SIZE_H #define PADDLE_MOBILE_TEST_LIB_SIZE_H
#include <vector>
#include <pthread.h> #include <pthread.h>
#include <thread> #include <thread>
#include <vector>
//#include <list> //#include <list>
//#include <tuple> //#include <tuple>
//#include <typeinfo> //#include <typeinfo>
...@@ -74,7 +74,7 @@ void foo() { ...@@ -74,7 +74,7 @@ void foo() {
// int z = 10; // int z = 10;
// } // }
// std::shared_ptr<int> s1 = std::make_shared<int>(); // std::shared_ptr<int> s1 = std::make_shared<int>();
// std::stringstream ss; // std::stringstream ss;
// ss << "12345"; // ss << "12345";
......
test/operators/test_batchnorm_op.cpp
浏览文件 @ dfa731e1
...@@ -137,7 +137,8 @@ int main() { ...@@ -137,7 +137,8 @@ int main() {
auto *inputx1_ptr = inputx1.data<float>(); auto *inputx1_ptr = inputx1.data<float>();
paddle_mobile::framework::Tensor mean; paddle_mobile::framework::Tensor mean;
SetupTensor<float>(&mean, {256}, static_cast<float>(0), static_cast<float>(1)); SetupTensor<float>(&mean, {256}, static_cast<float>(0),
static_cast<float>(1));
auto *mean_ptr = mean.data<float>(); auto *mean_ptr = mean.data<float>();
paddle_mobile::framework::Tensor scale; paddle_mobile::framework::Tensor scale;
...@@ -151,7 +152,8 @@ int main() { ...@@ -151,7 +152,8 @@ int main() {
auto *variance_ptr = variance.data<float>(); auto *variance_ptr = variance.data<float>();
paddle_mobile::framework::Tensor bias; paddle_mobile::framework::Tensor bias;
SetupTensor<float>(&bias, {256}, static_cast<float>(0), static_cast<float>(1)); SetupTensor<float>(&bias, {256}, static_cast<float>(0),
static_cast<float>(1));
auto *bias_ptr = bias.data<float>(); auto *bias_ptr = bias.data<float>();
paddle_mobile::framework::TestBatchNormOp<paddle_mobile::CPU> testBatchNormOp( paddle_mobile::framework::TestBatchNormOp<paddle_mobile::CPU> testBatchNormOp(
......
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