dneprDroid

const libname = "libSystem.B.dylib";

function CC_SHA1_Update(){
    //CC_SHA1_Update(CC_SHA1_CTX *c, const void *data, CC_LONG len);
    Interceptor.attach(Module.findExportByName(libname, "CC_SHA1_Update"),
    {
        onEnter: function(args) {
            var ccsha1update = {
                'operation': 'CC_SHA1_Update',

dneprDroid

gclient sync && \
rm -rf ./out && \ 
gn gen out/arm64 --args='target_os="ios" ios_enable_code_signing=false use_xcode_clang=true is_component_build=false rtc_include_tests=false is_debug=false target_cpu="arm64" rtc_libvpx_build_vp9=false enable_ios_bitcode=false use_goma=false rtc_enable_symbol_export=true enable_dsyms=true enable_stripping=true' && \
ninja -C out/arm64 sdk:framework_objc && \
rm -rf ~/Desktop/client-sdk-swift/Frameworks/WebRTC.xcframework && \ 
xcodebuild \
    -create-xcframework \
    -framework ./out/arm64/WebRTC.framework \
    -output ~/Desktop/client-sdk-swift/Frameworks/WebRTC.xcframework 

dneprDroid

@register_mil_to_nn_mapping(override=True)
def grid_sample(const_context, builder, op):
    image_name = make_input(const_context, builder, op.input)
    grid_name = make_input(const_context, builder, op.grid)
    out_name = op.outputs[0].name

    suffix = "_prepared"
    input_names1 = [grid_name]
    out_names1 = [out_name + suffix]

dneprDroid

@register_torch_op(torch_alias=["grid_sampler"], override=True)
def torch_grid_sample(context, node):
    inputs = mil_get_inputs(context, node, expected=5)
    res = mb.grid_sample(
        input=inputs[0], 
        grid=inputs[1], 
        mode=inputs[2], 
        padding_mode=inputs[3], 
        align_corners=inputs[4],
        name=node.name

dneprDroid

@register_torch_op(torch_alias=["grid_sampler"], override=True)
def torch_grid_sample(context, node):
    inputs = mil_get_inputs(context, node, expected=5)
    res = mb.grid_sample(
        input=inputs[0], 
        grid=inputs[1], 
        mode=inputs[2], 
        padding_mode=inputs[3], 
        align_corners=inputs[4],
        name=node.name

dneprDroid

IN_WH = 512
GRID_WH = 256

class TestModel(nn.Module):

    def forward(self, x, grid):
        grid_resized = self.resize_grid(grid)
        return F.grid_sample(
            x, grid_resized
        )

dneprDroid

sudo defaults write /Library/Preferences/com.apple.security.libraryvalidation.plist DisableLibraryValidation -bool true

dneprDroid

Config.Schema.API.methods[Config.Schema.API.methods.findIndex(x=>x.method=="messages.readHistory")].params = [{name: "emperor", type: "InputPeer"}, {name: "nmaid", type: "int"}]

dneprDroid

require 'nn'

torch.setdefaulttensortype('torch.FloatTensor')

function test_conv()
    local kernel_size = 3
    local stride = 1
    local padding = 1
    local layer = nn.SpatialConvolutionMM(64, 64, kernel_size, kernel_size, stride, stride, padding, padding)
    layer.weight:fill(2.2) -- fill weigths with 2.2

dneprDroid

extension BehaviorRelay where Element: RangeReplaceableCollection & MutableCollection, Element.Index == Int {

    func append(element: Element.Element) {
        var array = self.value
        array.append(element)
        self.accept(array)
    }

    func append<S: Sequence>(contentsOf collection: S) where S.Element == Element.Element {