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chore: clear the msvc compilation warning

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leejet
2023-10-28 20:55:24 +08:00
parent 3001c23f7d
commit 3bf1665885
3 changed files with 35 additions and 35 deletions
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48
stable-diffusion.cpp
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@@ -18,7 +18,7 @@
#include "rng_philox.h"
#include "stable-diffusion.h"
#define EPS 1e-05
#define EPS 1e-05f
static SDLogLevel log_level = SDLogLevel::INFO;
@@ -122,9 +122,9 @@ ggml_tensor* load_tensor_from_file(ggml_context* ctx, const std::string& file_pa
}
void ggml_tensor_set_f32_randn(struct ggml_tensor* tensor, std::shared_ptr<RNG> rng) {
uint32_t n = ggml_nelements(tensor);
uint32_t n = (uint32_t)ggml_nelements(tensor);
std::vector<float> random_numbers = rng->randn(n);
for (int i = 0; i < n; i++) {
for (uint32_t i = 0; i < n; i++) {
ggml_set_f32_1d(tensor, i, random_numbers[i]);
}
}
@@ -438,12 +438,12 @@ std::vector<std::pair<std::string, float>> parse_prompt_attention(const std::str
std::string weight = m[1];
if (text == "(") {
round_brackets.push_back(res.size());
round_brackets.push_back((int)res.size());
} else if (text == "[") {
square_brackets.push_back(res.size());
square_brackets.push_back((int)res.size());
} else if (!weight.empty()) {
if (!round_brackets.empty()) {
multiply_range(round_brackets.back(), std::stod(weight));
multiply_range(round_brackets.back(), std::stof(weight));
round_brackets.pop_back();
}
} else if (text == ")" && !round_brackets.empty()) {
@@ -2707,13 +2707,13 @@ struct DiscreteSchedule : SigmaSchedule {
if (n == 0) {
return result;
} else if (n == 1) {
result.push_back(t_to_sigma(t_max));
result.push_back(t_to_sigma((float)t_max));
result.push_back(0);
return result;
}
float step = static_cast<float>(t_max) / static_cast<float>(n - 1);
for (int i = 0; i < n; ++i) {
for (uint32_t i = 0; i < n; ++i) {
float t = t_max - step * i;
result.push_back(t_to_sigma(t));
}
@@ -2726,17 +2726,17 @@ struct KarrasSchedule : SigmaSchedule {
std::vector<float> get_sigmas(uint32_t n) {
// These *COULD* be function arguments here,
// but does anybody ever bother to touch them?
float sigma_min = 0.1;
float sigma_max = 10.;
float rho = 7.;
float sigma_min = 0.1f;
float sigma_max = 10.f;
float rho = 7.f;
std::vector<float> result(n + 1);
float min_inv_rho = pow(sigma_min, (1. / rho));
float max_inv_rho = pow(sigma_max, (1. / rho));
for (int i = 0; i < n; i++) {
float min_inv_rho = pow(sigma_min, (1.f / rho));
float max_inv_rho = pow(sigma_max, (1.f / rho));
for (uint32_t i = 0; i < n; i++) {
// Eq. (5) from Karras et al 2022
result[i] = pow(max_inv_rho + (float)i / ((float)n - 1.) * (min_inv_rho - max_inv_rho), rho);
result[i] = pow(max_inv_rho + (float)i / ((float)n - 1.f) * (min_inv_rho - max_inv_rho), rho);
}
result[n] = 0.;
return result;
@@ -3748,7 +3748,7 @@ class StableDiffusionGGML {
}
} else {
// DPM-Solver-2
float sigma_mid = exp(0.5 * (log(sigmas[i]) + log(sigmas[i + 1])));
float sigma_mid = exp(0.5f * (log(sigmas[i]) + log(sigmas[i + 1])));
float dt_1 = sigma_mid - sigmas[i];
float dt_2 = sigmas[i + 1] - sigmas[i];
@@ -3811,7 +3811,7 @@ class StableDiffusionGGML {
float t = t_fn(sigmas[i]);
float t_next = t_fn(sigma_down);
float h = t_next - t;
float s = t + 0.5 * h;
float s = t + 0.5f * h;
float* vec_d = (float*)d->data;
float* vec_x = (float*)x->data;
@@ -3820,7 +3820,7 @@ class StableDiffusionGGML {
// First half-step
for (int j = 0; j < ggml_nelements(x); j++) {
vec_x2[j] = (sigma_fn(s) / sigma_fn(t)) * vec_x[j] - (exp(-h * 0.5) - 1) * vec_denoised[j];
vec_x2[j] = (sigma_fn(s) / sigma_fn(t)) * vec_x[j] - (exp(-h * 0.5f) - 1) * vec_denoised[j];
}
denoise(x2, sigmas[i + 1], i + 1);
@@ -3862,7 +3862,7 @@ class StableDiffusionGGML {
float t_next = t_fn(sigmas[i + 1]);
float h = t_next - t;
float a = sigmas[i + 1] / sigmas[i];
float b = exp(-h) - 1.;
float b = exp(-h) - 1.f;
float* vec_x = (float*)x->data;
float* vec_denoised = (float*)denoised->data;
float* vec_old_denoised = (float*)old_denoised->data;
@@ -3876,7 +3876,7 @@ class StableDiffusionGGML {
float h_last = t - t_fn(sigmas[i - 1]);
float r = h_last / h;
for (int j = 0; j < ggml_nelements(x); j++) {
float denoised_d = (1. + 1. / (2. * r)) * vec_denoised[j] - (1. / (2. * r)) * vec_old_denoised[j];
float denoised_d = (1.f + 1.f / (2.f * r)) * vec_denoised[j] - (1.f / (2.f * r)) * vec_old_denoised[j];
vec_x[j] = a * vec_x[j] - b * denoised_d;
}
}
@@ -3910,7 +3910,7 @@ class StableDiffusionGGML {
if (i == 0 || sigmas[i + 1] == 0) {
// Simpler step for the edge cases
float b = exp(-h) - 1.;
float b = exp(-h) - 1.f;
for (int j = 0; j < ggml_nelements(x); j++) {
vec_x[j] = a * vec_x[j] - b * vec_denoised[j];
}
@@ -3919,10 +3919,10 @@ class StableDiffusionGGML {
float h_min = std::min(h_last, h);
float h_max = std::max(h_last, h);
float r = h_max / h_min;
float h_d = (h_max + h_min) / 2.;
float b = exp(-h_d) - 1.;
float h_d = (h_max + h_min) / 2.f;
float b = exp(-h_d) - 1.f;
for (int j = 0; j < ggml_nelements(x); j++) {
float denoised_d = (1. + 1. / (2. * r)) * vec_denoised[j] - (1. / (2. * r)) * vec_old_denoised[j];
float denoised_d = (1.f + 1.f / (2.f * r)) * vec_denoised[j] - (1.f / (2.f * r)) * vec_old_denoised[j];
vec_x[j] = a * vec_x[j] - b * denoised_d;
}
}