本文整理匯總了TypeScript中@tensorflow/tfjs-core.add函數的典型用法代碼示例。如果您正苦於以下問題：TypeScript add函數的具體用法？TypeScript add怎麽用？TypeScript add使用的例子？那麽, 這裏精選的函數代碼示例或許可以為您提供幫助。
在下文中一共展示了add函數的10個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的TypeScript代碼示例。
示例1: dLoss
// Define losses.
dLoss(truePred: tf.Tensor1D, generatedPred: tf.Tensor1D) {
if (this.lossType === 'LeastSq loss') {
return tf.add(
truePred.sub(tf.scalar(1)).square().mean(),
generatedPred.square().mean()
) as tf.Scalar;
} else {
return tf.add(
truePred.log().mul(tf.scalar(0.95)).mean(),
tf.sub(tf.scalar(1), generatedPred).log().mean()
).mul(tf.scalar(-1)) as tf.Scalar;
}
}示例2:
return tf.tidy(() => {
let out = tf.conv2d(x, params.filters, strides, 'same')
out = tf.add(out, params.batch_norm_offset)
return tf.clipByValue(out, 0, 6)
})示例3: residual
export function residual(x: tf.Tensor4D, params: ResidualLayerParams): tf.Tensor4D {
let out = conv(x, params.conv1)
out = convNoRelu(out, params.conv2)
out = tf.add(out, x)
out = tf.relu(out)
return out
}示例4: residualDown
export function residualDown(x: tf.Tensor4D, params: ResidualLayerParams): tf.Tensor4D {
let out = convDown(x, params.conv1)
out = convNoRelu(out, params.conv2)
let pooled = tf.avgPool(x, 2, 2, 'valid') as tf.Tensor4D
const zeros = tf.zeros<tf.Rank.R4>(pooled.shape)
const isPad = pooled.shape[3] !== out.shape[3]
const isAdjustShape = pooled.shape[1] !== out.shape[1] || pooled.shape[2] !== out.shape[2]
if (isAdjustShape) {
const padShapeX = [...out.shape] as [number, number, number, number]
padShapeX[1] = 1
const zerosW = tf.zeros<tf.Rank.R4>(padShapeX)
out = tf.concat([out, zerosW], 1)
const padShapeY = [...out.shape] as [number, number, number, number]
padShapeY[2] = 1
const zerosH = tf.zeros<tf.Rank.R4>(padShapeY)
out = tf.concat([out, zerosH], 2)
}
pooled = isPad ? tf.concat([pooled, zeros], 3) : pooled
out = tf.add(pooled, out) as tf.Tensor4D
out = tf.relu(out)
return out
}示例5:
return tf.tidy(() => {
const out = tf.add(
tf.conv2d(x, params.filters, [1, 1], padding),
params.bias
) as tf.Tensor4D
return withRelu ? tf.relu(out) : out
})示例6: getCenterCoordinatesAndSizesLayer
function getCenterCoordinatesAndSizesLayer(x: tf.Tensor2D) {
const vec = tf.unstack(tf.transpose(x, [1, 0]))
const sizes = [
tf.sub(vec[2], vec[0]),
tf.sub(vec[3], vec[1])
]
const centers = [
tf.add(vec[0], tf.div(sizes[0], tf.scalar(2))),
tf.add(vec[1], tf.div(sizes[1], tf.scalar(2)))
]
return {
sizes,
centers
}
}示例7: convLayer
function convLayer(
x: tf.Tensor4D,
params: ConvLayerParams,
strides: [number, number],
withRelu: boolean,
padding: 'valid' | 'same' = 'same'
): tf.Tensor4D {
const { filters, bias } = params.conv
let out = tf.conv2d(x, filters, strides, padding)
out = tf.add(out, bias)
out = scale(out, params.scale)
return withRelu ? tf.relu(out) : out
}示例8: decodeBoxesLayer
function decodeBoxesLayer(x0: tf.Tensor2D, x1: tf.Tensor2D) {
const {
sizes,
centers
} = getCenterCoordinatesAndSizesLayer(x0)
const vec = tf.unstack(tf.transpose(x1, [1, 0]))
const div0_out = tf.div(tf.mul(tf.exp(tf.div(vec[2], tf.scalar(5))), sizes[0]), tf.scalar(2))
const add0_out = tf.add(tf.mul(tf.div(vec[0], tf.scalar(10)), sizes[0]), centers[0])
const div1_out = tf.div(tf.mul(tf.exp(tf.div(vec[3], tf.scalar(5))), sizes[1]), tf.scalar(2))
const add1_out = tf.add(tf.mul(tf.div(vec[1], tf.scalar(10)), sizes[1]), centers[1])
return tf.transpose(
tf.stack([
tf.sub(add0_out, div0_out),
tf.sub(add1_out, div1_out),
tf.add(add0_out, div0_out),
tf.add(add1_out, div1_out)
]),
[1, 0]
)
}示例9: scale
export function scale(x: tf.Tensor4D, params: ScaleLayerParams): tf.Tensor4D {
return tf.add(tf.mul(x, params.weights), params.biases)
}示例10:
return tf.tidy(() =>
tf.add(
tf.matMul(x, params.weights),
params.bias
)