This restriction causes me to be unable to use Metal to create images and simultaneously use Swift to add UI controls or RealityKit content (without using a window) in immersive mode.
_rdy
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Screenshot:
Specific error message:
validateComputeFunctionArguments:1149: failed assertion `Compute Function(textureShader): Shader uses texture(texture[0]) as read-write, but hardware does not support read-write texture of this pixel format.'
OS: visionOS 2.1 (22N5548c) simulator.
Link:
https://developer.apple.com/documentation/visionos/generating-procedural-textures-in-visionos
VStack(spacing: 8) {
}
.padding(20)
.frame(width: 320)
.glassBackgroundEffect()
.cornerRadius(10)
UI:
Attachment(id: "tooptip") {
if isRecording {
TooltipView {
HStack(spacing: 8) {
Image(systemName: "waveform")
.font(.title)
.frame(minWidth: 100)
}
}
.transition(.opacity.combined(with: .scale))
}
}
Trigger:
Button("Toggle") {
withAnimation{
isRecording.toggle()
}
}
The above code did not show the animation effect when running. When I use isRecording to drive an element in a common SwiftUI view, there is an animation effect.
func testMLTensor() {
let t1 = MLTensor(shape: [2000, 1], scalars: [Float](repeating: Float.random(in: 0.0...10.0), count: 2000), scalarType: Float.self)
let t2 = MLTensor(shape: [1, 3000], scalars: [Float](repeating: Float.random(in: 0.0...10.0), count: 3000), scalarType: Float.self)
for _ in 0...50 {
let t = Date()
let x = (t1 * t2)
print("MLTensor", t.timeIntervalSinceNow * 1000, "ms")
}
}
testMLTensor()
The above code took more time than expected, especially in the early stage of iteration.
func testMLTensor() {
let t1 = MLTensor(shape: [2000, 1], scalars: [Float](repeating: Float.random(in: 0.0...10.0), count: 2000), scalarType: Float.self)
let t2 = MLTensor(shape: [1, 3000], scalars: [Float](repeating: Float.random(in: 0.0...10.0), count: 3000), scalarType: Float.self)
for _ in 0...50 {
let t = Date()
let x = (t1 * t2)
print("MLTensor", t.timeIntervalSinceNow * 1000, "ms")
}
}
testMLTensor()
The above code took more time than expected, especially in the early stage of iteration.
func testMLTensor() {
let t1 = MLTensor(shape: [2000, 1], scalars: [Float](repeating: Float.random(in: 0.0...10.0), count: 2000), scalarType: Float.self)
let t2 = MLTensor(shape: [1, 3000], scalars: [Float](repeating: Float.random(in: 0.0...10.0), count: 3000), scalarType: Float.self)
for _ in 0...50 {
let t = Date()
let x = (t1 * t2)
print("MLTensor", t.timeIntervalSinceNow * 1000, "ms")
}
}
testMLTensor()
The above code took more time than expected, especially in the early stage of iteration.