/**
 * @license
 * Copyright 2019 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
import { ENGINE } from './engine';
import * as tf from './index';
import { ALL_ENVS, describeWithFlags } from './jasmine_util';
import { expectArraysClose } from './test_util';
describeWithFlags('gradients', ALL_ENVS, () => {
    it('matmul + relu', async () => {
        const a = tf.tensor2d([-1, 2, -3, 10, -20, 30], [2, 3]);
        const b = tf.tensor2d([2, -3, 4, -1, 2, -3], [3, 2]);
        const [da, db] = tf.grads((a, b) => {
            // m = dot(a, b)
            // y = relu(m)
            // e = sum(y)
            const m = tf.matMul(a, b);
            const y = tf.relu(m);
            return tf.sum(y);
        })([a, b]);
        // de/dy = 1
        // dy/dm = step(m)
        // de/dm = de/dy * dy/dm = step(m)
        const dedm = tf.step(tf.matMul(a, b));
        // de/da = dot(de/dy, bT)
        expect(da.shape).toEqual(a.shape);
        let transposeA = false;
        let transposeB = true;
        expectArraysClose(await da.data(), await tf.matMul(dedm, b, transposeA, transposeB).data());
        // de/db = dot(aT, de/dy)
        expect(db.shape).toEqual(b.shape);
        transposeA = true;
        transposeB = false;
        expectArraysClose(await db.data(), await tf.matMul(a, dedm, transposeA, transposeB).data());
    });
    it('grad(f)', async () => {
        const grad = tf.grad(x => x.square());
        const result = grad(tf.tensor1d([.1, .2]));
        expectArraysClose(await result.data(), [.2, .4]);
    });
    it('calling grad(f) twice works', async () => {
        const grad = tf.grad(x => x.square());
        const result = grad(tf.tensor1d([.1, .2]));
        const result2 = grad(tf.tensor1d([.1, .4]));
        expectArraysClose(await result.data(), [.2, .4]);
        expectArraysClose(await result2.data(), [.2, .8]);
    });
    it('grad(f): throwing an error during forward pass', () => {
        const grad = tf.grad(x => {
            throw new Error('failed forward pass');
        });
        expect(() => grad(tf.zeros([]))).toThrowError();
        expect(ENGINE.isTapeOn()).toBe(false);
    });
    it('grad(f): throwing an error during backwards pass', () => {
        const customOp = tf.customGrad((x) => {
            return {
                value: x,
                gradFunc: () => {
                    throw new Error('failed backward pass');
                }
            };
        });
        const grad = tf.grad(x => customOp(x));
        expect(() => grad(tf.zeros([]))).toThrowError();
        expect(ENGINE.isTapeOn()).toBe(false);
    });
    it('grads(f)', async () => {
        const grads = tf.grads(x => x.square());
        const result = grads([tf.tensor1d([.1, .2])]);
        expectArraysClose(await result[0].data(), [.2, .4]);
    });
    it('calling grads(f) twice works', async () => {
        const grads = tf.grads(x => x.square());
        const result = grads([tf.tensor1d([.1, .2])]);
        const result2 = grads([tf.tensor1d([.1, .4])]);
        expectArraysClose(await result[0].data(), [.2, .4]);
        expectArraysClose(await result2[0].data(), [.2, .8]);
    });
    it('works with reshape', async () => {
        const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);
        const exponent = tf.tensor1d([2, 2, 2, 2], 'int32');
        const da = tf.grad(a => {
            const b = a.flatten();
            const m = tf.pow(b, exponent);
            return tf.sum(m);
        })(a);
        expect(da.shape).toEqual([2, 2]);
        expectArraysClose(await da.data(), [2, 4, 6, 8]);
    });
    it('reshape outside tf.grads() throws error', () => {
        const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);
        const b = a.flatten();
        const exponent = tf.tensor1d([2, 2, 2, 2], 'int32');
        const f = () => {
            tf.grads((a, b) => {
                const m = tf.pow(b, exponent);
                return tf.sum(m);
            })([a, b]);
        };
        expect(f).toThrowError();
    });
    it('does not error if irrelevant (pruned) ops are missing grads', async () => {
        const a = tf.tensor1d([true, true], 'bool');
        const b = tf.tensor1d([false, true], 'bool');
        const da = tf.grad(a => {
            // Logical has no gradients, but it is irrelevant.
            a.logicalAnd(b);
            return a.sum();
        })(a);
        expectArraysClose(await da.data(), [1, 1]);
    });
    it('errors if relevant ops are missing grads', () => {
        const a = tf.tensor1d([true, true], 'bool');
        const b = tf.tensor1d([false, true], 'bool');
        const dfda = tf.grad(a => {
            // Logical has no gradients, but it's relevant to the output.
            return a.logicalAnd(b);
        });
        expect(() => dfda(a)).toThrowError();
    });
    it('works with asType', async () => {
        const a = tf.tensor2d([1, 2, 3, 4], [2, 2], 'int32');
        const exponent = tf.tensor2d([2, 2, 2, 2], [2, 2], 'int32');
        const da = tf.grad(a => {
            const b = a.toFloat();
            const m = tf.pow(b, exponent);
            return tf.sum(m);
        })(a);
        expect(da.shape).toEqual([2, 2]);
        expect(da.dtype).toEqual('float32');
        expectArraysClose(await da.data(), [2, 4, 6, 8]);
    });
    it('asType outside of tf.grads() throws error', () => {
        const a = tf.tensor2d([1, 2, 3, 4], [2, 2], 'int32');
        const b = a.toFloat();
        const exponent = tf.tensor2d([2, 2, 2, 2], [2, 2], 'int32');
        const f = () => {
            tf.grad(a => {
                const m = tf.pow(b, exponent);
                return tf.sum(m);
            })(a);
        };
        expect(f).toThrowError();
    });
    it('saves tensors from the forward pass as expected', () => {
        const x = tf.scalar(1).variable();
        const optimizer = tf.train.sgd(0.1);
        optimizer.minimize(() => {
            const y = x.square();
            const z = y.square();
            y.dispose();
            return z;
        });
    });
    it('custom ops do not leak', () => {
        const before = tf.memory().numTensors;
        const x = tf.softmax([1, 2, 3, 4]);
        x.dispose();
        const now = tf.memory().numTensors;
        expect(now).toBe(before);
    });
});
describeWithFlags('valueAndGradients', ALL_ENVS, () => {
    it('matmul + relu', async () => {
        const a = tf.tensor2d([-1, 2, -3, 10, -20, 30], [2, 3]);
        const b = tf.tensor2d([2, -3, 4, -1, 2, -3], [3, 2]);
        const { value, grads } = tf.valueAndGrads((a, b) => {
            // m = dot(a, b)
            // y = relu(m)
            // e = sum(y)
            const m = tf.matMul(a, b);
            const y = tf.relu(m);
            return tf.sum(y);
        })([a, b]);
        expectArraysClose(await value.data(), 10);
        // de/dy = 1
        // dy/dm = step(m)
        // de/dm = de/dy * dy/dm = step(m)
        const dedm = tf.step(tf.matMul(a, b));
        const [da, db] = grads;
        // de/da = dot(de/dy, bT)
        let transposeA = false;
        let transposeB = true;
        expectArraysClose(await da.data(), await tf.matMul(dedm, b, transposeA, transposeB).data());
        // de/db = dot(aT, de/dy)
        transposeA = true;
        transposeB = false;
        expectArraysClose(await db.data(), await tf.matMul(a, dedm, transposeA, transposeB).data());
    });
    it('matmul + relu + inner tidy', async () => {
        const a = tf.tensor2d([-1, 2, -3, 10, -20, 30], [2, 3]);
        const b = tf.tensor2d([2, -3, 4, -1, 2, -3], [3, 2]);
        const { value, grads } = tf.valueAndGrads((a, b) => {
            // m = dot(a, b)
            // y = relu(m)
            // e = sum(y)
            const m = tf.matMul(a, b);
            return tf.tidy(() => {
                const y = tf.relu(m);
                return tf.sum(y);
            });
        })([a, b]);
        expectArraysClose(await value.data(), 10);
        // de/dy = 1
        // dy/dm = step(m)
        // de/dm = de/dy * dy/dm = step(m)
        const dedm = tf.step(tf.matMul(a, b));
        const [da, db] = grads;
        // de/da = dot(de/dy, bT)
        let transposeA = false;
        let transposeB = true;
        expectArraysClose(await da.data(), await tf.matMul(dedm, b, transposeA, transposeB).data());
        // de/db = dot(aT, de/dy)
        transposeA = true;
        transposeB = false;
        expectArraysClose(await db.data(), await tf.matMul(a, dedm, transposeA, transposeB).data());
    });
});
describeWithFlags('higher-order gradients', ALL_ENVS, () => {
    it('grad(grad(f))', async () => {
        const x = tf.tensor1d([.1, .2]);
        const before = tf.memory().numTensors;
        const gradgrad = tf.grad(tf.grad(x => x.mul(x).mul(x)));
        const result = gradgrad(x);
        expect(tf.memory().numTensors).toBe(before + 1);
        expectArraysClose(await result.data(), [.6, 1.2]);
    });
    it('grad(grad(x^2))', async () => {
        const x = tf.scalar(3);
        const gradgrad = tf.grad(tf.grad(x => x.square()));
        const result = gradgrad(x);
        // grad(grad(x^2)) = grad(2x) = 2
        expectArraysClose(await result.data(), [2]);
    });
    it('grads(grads(f))', async () => {
        const grads = tf.grads(x => x.mul(x).mul(x));
        const gradsgrads = tf.grads(x => grads([x])[0]);
        const result = gradsgrads([tf.tensor1d([.1, .2])]);
        expectArraysClose(await result[0].data(), [.6, 1.2]);
    });
});
describeWithFlags('customGradient', ALL_ENVS, () => {
    it('basic', async () => {
        const a = tf.scalar(3);
        const b = tf.scalar(2, 'int32');
        const dy = tf.scalar(4);
        const customPow = tf.customGrad((a) => {
            const value = tf.pow(a, b);
            const gradFunc = (dy) => dy.mul(tf.scalar(0.1));
            return { value, gradFunc };
        });
        const { value, grad } = tf.valueAndGrad(a => customPow(a))(a, dy);
        expect(value.shape).toEqual(a.shape);
        expectArraysClose(await value.data(), [9]);
        expect(grad.shape).toEqual(a.shape);
        expectArraysClose(await grad.data(), [.4]);
    });
    it('second order derivative through customGradient', async () => {
        const a = tf.scalar(3);
        const b = tf.scalar(2, 'int32');
        const dy = tf.scalar(5);
        const customPow = tf.customGrad((a, save) => {
            const value = tf.pow(a, b);
            save([a]);
            const gradFunc = (dy, saved) => {
                const [a] = saved;
                return dy.mul(a);
            };
            return { value, gradFunc };
        });
        const dda = tf.grad(tf.grad(a => customPow(a)))(a, dy);
        expect(dda.shape).toEqual(a.shape);
        // First order: dy * a. Second order: dy.
        expectArraysClose(await dda.data(), await dy.data());
    });
    it('calling gradient of custom op twice works', async () => {
        const customOp = tf.customGrad((x, save) => {
            // Override gradient of our custom x ^ 2 op to be dy * abs(x);
            save([x]);
            return {
                value: x.square(),
                gradFunc: (dy, saved) => {
                    const [x] = saved;
                    return dy.mul(x.abs());
                }
            };
        });
        const x = tf.tensor1d([-1, -2, 3]);
        const grad = tf.grad(x => customOp(x));
        expectArraysClose(await grad(x).data(), [1, 2, 3]);
        expectArraysClose(await grad(x).data(), [1, 2, 3]);
    });
});
//# sourceMappingURL=data:application/json;base64,{"version":3,"file":"gradients_test.js","sourceRoot":"","sources":["../../../../../tfjs-core/src/gradients_test.ts"],"names":[],"mappings":"AACA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,EAAC,MAAM,EAAC,MAAM,UAAU,CAAC;AAChC,OAAO,KAAK,EAAE,MAAM,SAAS,CAAC;AAC9B,OAAO,EAAC,QAAQ,EAAE,iBAAiB,EAAC,MAAM,gBAAgB,CAAC;AAE3D,OAAO,EAAC,iBAAiB,EAAC,MAAM,aAAa,CAAC;AAE9C,iBAAiB,CAAC,WAAW,EAAE,QAAQ,EAAE,GAAG,EAAE;IAC5C,EAAE,CAAC,eAAe,EAAE,KAAK,IAAI,EAAE;QAC7B,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACxD,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAErD,MAAM,CAAC,EAAE,EAAE,EAAE,CAAC,GAAG,EAAE,CAAC,KAAK,CAAC,CAAC,CAAc,EAAE,CAAc,EAAE,EAAE;YAC3D,gBAAgB;YAChB,cAAc;YACd,aAAa;YACb,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC;YAC1B,MAAM,CAAC,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,CAAC;YACrB,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;QACnB,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAEX,YAAY;QACZ,kBAAkB;QAClB,kCAAkC;QAClC,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAEtC,yBAAyB;QACzB,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QAClC,IAAI,UAAU,GAAG,KAAK,CAAC;QACvB,IAAI,UAAU,GAAG,IAAI,CAAC;QACtB,iBAAiB,CACb,MAAM,EAAE,CAAC,IAAI,EAAE,EACf,MAAM,EAAE,CAAC,MAAM,CAAC,IAAI,EAAE,CAAC,EAAE,UAAU,EAAE,UAAU,CAAC,CAAC,IAAI,EAAE,CAAC,CAAC;QAE7D,yBAAyB;QACzB,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QAClC,UAAU,GAAG,IAAI,CAAC;QAClB,UAAU,GAAG,KAAK,CAAC;QACnB,iBAAiB,CACb,MAAM,EAAE,CAAC,IAAI,EAAE,EACf,MAAM,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,IAAI,EAAE,UAAU,EAAE,UAAU,CAAC,CAAC,IAAI,EAAE,CAAC,CAAC;IAC/D,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,SAAS,EAAE,KAAK,IAAI,EAAE;QACvB,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,MAAM,EAAE,CAAC,CAAC;QACtC,MAAM,MAAM,GAAG,IAAI,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC;QAC3C,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC;IACnD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,6BAA6B,EAAE,KAAK,IAAI,EAAE;QAC3C,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,MAAM,EAAE,CAAC,CAAC;QAEtC,MAAM,MAAM,GAAG,IAAI,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC;QAC3C,MAAM,OAAO,GAAG,IAAI,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC;QAC5C,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC;QACjD,iBAAiB,CAAC,MAAM,OAAO,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC;IACpD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,gDAAgD,EAAE,GAAG,EAAE;QACxD,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE;YACvB,MAAM,IAAI,KAAK,CAAC,qBAAqB,CAAC,CAAC;QACzC,CAAC,CAAC,CAAC;QACH,MAAM,CAAC,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,KAAK,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,YAAY,EAAE,CAAC;QAChD,MAAM,CAAC,MAAM,CAAC,QAAQ,EAAE,CAAC,CAAC,IAAI,CAAC,KAAK,CAAC,CAAC;IACxC,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,kDAAkD,EAAE,GAAG,EAAE;QAC1D,MAAM,QAAQ,GAAG,EAAE,CAAC,UAAU,CAAC,CAAC,CAAY,EAAE,EAAE;YAC9C,OAAO;gBACL,KAAK,EAAE,CAAC;gBACR,QAAQ,EAAE,GAAG,EAAE;oBACb,MAAM,IAAI,KAAK,CAAC,sBAAsB,CAAC,CAAC;gBAC1C,CAAC;aACF,CAAC;QACJ,CAAC,CAAC,CAAC;QACH,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,CAAC,CAAC;QACvC,MAAM,CAAC,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,KAAK,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,YAAY,EAAE,CAAC;QAChD,MAAM,CAAC,MAAM,CAAC,QAAQ,EAAE,CAAC,CAAC,IAAI,CAAC,KAAK,CAAC,CAAC;IACxC,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,UAAU,EAAE,KAAK,IAAI,EAAE;QACxB,MAAM,KAAK,GAAG,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,MAAM,EAAE,CAAC,CAAC;QACxC,MAAM,MAAM,GAAG,KAAK,CAAC,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;QAC9C,iBAAiB,CAAC,MAAM,MAAM,CAAC,CAAC,CAAC,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC;IACtD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,8BAA8B,EAAE,KAAK,IAAI,EAAE;QAC5C,MAAM,KAAK,GAAG,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,MAAM,EAAE,CAAC,CAAC;QAExC,MAAM,MAAM,GAAG,KAAK,CAAC,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;QAC9C,MAAM,OAAO,GAAG,KAAK,CAAC,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;QAC/C,iBAAiB,CAAC,MAAM,MAAM,CAAC,CAAC,CAAC,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC;QACpD,iBAAiB,CAAC,MAAM,OAAO,CAAC,CAAC,CAAC,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC;IACvD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,oBAAoB,EAAE,KAAK,IAAI,EAAE;QAClC,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAC5C,MAAM,QAAQ,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QAEpD,MAAM,EAAE,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE;YACrB,MAAM,CAAC,GAAG,CAAC,CAAC,OAAO,EAAE,CAAC;YACtB,MAAM,CAAC,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,QAAQ,CAAC,CAAC;YAC9B,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;QACnB,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;QAEN,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACjC,iBAAiB,CAAC,MAAM,EAAE,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;IACnD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,yCAAyC,EAAE,GAAG,EAAE;QACjD,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAC5C,MAAM,CAAC,GAAG,CAAC,CAAC,OAAO,EAAE,CAAC;QACtB,MAAM,QAAQ,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QAEpD,MAAM,CAAC,GAAG,GAAG,EAAE;YACb,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,EAAE;gBAChB,MAAM,CAAC,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,QAAQ,CAAC,CAAC;gBAC9B,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;YACnB,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACb,CAAC,CAAC;QACF,MAAM,CAAC,CAAC,CAAC,CAAC,YAAY,EAAE,CAAC;IAC3B,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,6DAA6D,EAC7D,KAAK,IAAI,EAAE;QACT,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,IAAI,EAAE,IAAI,CAAC,EAAE,MAAM,CAAC,CAAC;QAC5C,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,KAAK,EAAE,IAAI,CAAC,EAAE,MAAM,CAAC,CAAC;QAC7C,MAAM,EAAE,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE;YACrB,kDAAkD;YAClD,CAAC,CAAC,UAAU,CAAC,CAAC,CAAC,CAAC;YAChB,OAAO,CAAC,CAAC,GAAG,EAAE,CAAC;QACjB,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;QACN,iBAAiB,CAAC,MAAM,EAAE,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;IAC7C,CAAC,CAAC,CAAC;IAEN,EAAE,CAAC,0CAA0C,EAAE,GAAG,EAAE;QAClD,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,IAAI,EAAE,IAAI,CAAC,EAAE,MAAM,CAAC,CAAC;QAC5C,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,KAAK,EAAE,IAAI,CAAC,EAAE,MAAM,CAAC,CAAC;QAC7C,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE;YACvB,6DAA6D;YAC7D,OAAO,CAAC,CAAC,UAAU,CAAC,CAAC,CAAC,CAAC;QACzB,CAAC,CAAC,CAAC;QACH,MAAM,CAAC,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,CAAC,CAAC,YAAY,EAAE,CAAC;IACvC,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,mBAAmB,EAAE,KAAK,IAAI,EAAE;QACjC,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QACrD,MAAM,QAAQ,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QAE5D,MAAM,EAAE,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE;YACrB,MAAM,CAAC,GAAG,CAAC,CAAC,OAAO,EAAE,CAAC;YACtB,MAAM,CAAC,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,QAAQ,CAAC,CAAC;YAC9B,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;QACnB,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;QAEN,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACjC,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,SAAS,CAAC,CAAC;QACpC,iBAAiB,CAAC,MAAM,EAAE,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;IACnD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,2CAA2C,EAAE,GAAG,EAAE;QACnD,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QACrD,MAAM,CAAC,GAAG,CAAC,CAAC,OAAO,EAAE,CAAC;QACtB,MAAM,QAAQ,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QAE5D,MAAM,CAAC,GAAG,GAAG,EAAE;YACb,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE;gBACV,MAAM,CAAC,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,QAAQ,CAAC,CAAC;gBAC9B,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;YACnB,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;QACR,CAAC,CAAC;QACF,MAAM,CAAC,CAAC,CAAC,CAAC,YAAY,EAAE,CAAC;IAC3B,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,iDAAiD,EAAE,GAAG,EAAE;QACzD,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC,QAAQ,EAAE,CAAC;QAClC,MAAM,SAAS,GAAG,EAAE,CAAC,KAAK,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;QACpC,SAAS,CAAC,QAAQ,CAAC,GAAG,EAAE;YACtB,MAAM,CAAC,GAAG,CAAC,CAAC,MAAM,EAAE,CAAC;YACrB,MAAM,CAAC,GAAG,CAAC,CAAC,MAAM,EAAE,CAAC;YACrB,CAAC,CAAC,OAAO,EAAE,CAAC;YACZ,OAAO,CAAC,CAAC;QACX,CAAC,CAAC,CAAC;IACL,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,wBAAwB,EAAE,GAAG,EAAE;QAChC,MAAM,MAAM,GAAG,EAAE,CAAC,MAAM,EAAE,CAAC,UAAU,CAAC;QACtC,MAAM,CAAC,GAAG,EAAE,CAAC,OAAO,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACnC,CAAC,CAAC,OAAO,EAAE,CAAC;QACZ,MAAM,GAAG,GAAG,EAAE,CAAC,MAAM,EAAE,CAAC,UAAU,CAAC;QACnC,MAAM,CAAC,GAAG,CAAC,CAAC,IAAI,CAAC,MAAM,CAAC,CAAC;IAC3B,CAAC,CAAC,CAAC;AACL,CAAC,CAAC,CAAC;AAEH,iBAAiB,CAAC,mBAAmB,EAAE,QAAQ,EAAE,GAAG,EAAE;IACpD,EAAE,CAAC,eAAe,EAAE,KAAK,IAAI,EAAE;QAC7B,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACxD,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAErD,MAAM,EAAC,KAAK,EAAE,KAAK,EAAC,GAChB,EAAE,CAAC,aAAa,CAAC,CAAC,CAAc,EAAE,CAAc,EAAE,EAAE;YAClD,gBAAgB;YAChB,cAAc;YACd,aAAa;YACb,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC;YAC1B,MAAM,CAAC,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,CAAC;YACrB,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;QACnB,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAEf,iBAAiB,CAAC,MAAM,KAAK,CAAC,IAAI,EAAE,EAAE,EAAE,CAAC,CAAC;QAE1C,YAAY;QACZ,kBAAkB;QAClB,kCAAkC;QAClC,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAEtC,MAAM,CAAC,EAAE,EAAE,EAAE,CAAC,GAAG,KAAK,CAAC;QACvB,yBAAyB;QACzB,IAAI,UAAU,GAAG,KAAK,CAAC;QACvB,IAAI,UAAU,GAAG,IAAI,CAAC;QACtB,iBAAiB,CACb,MAAM,EAAE,CAAC,IAAI,EAAE,EACf,MAAM,EAAE,CAAC,MAAM,CAAC,IAAI,EAAE,CAAC,EAAE,UAAU,EAAE,UAAU,CAAC,CAAC,IAAI,EAAE,CAAC,CAAC;QAE7D,yBAAyB;QACzB,UAAU,GAAG,IAAI,CAAC;QAClB,UAAU,GAAG,KAAK,CAAC;QACnB,iBAAiB,CACb,MAAM,EAAE,CAAC,IAAI,EAAE,EACf,MAAM,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,IAAI,EAAE,UAAU,EAAE,UAAU,CAAC,CAAC,IAAI,EAAE,CAAC,CAAC;IAC/D,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,4BAA4B,EAAE,KAAK,IAAI,EAAE;QAC1C,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACxD,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAErD,MAAM,EAAC,KAAK,EAAE,KAAK,EAAC,GAChB,EAAE,CAAC,aAAa,CAAC,CAAC,CAAc,EAAE,CAAc,EAAE,EAAE;YAClD,gBAAgB;YAChB,cAAc;YACd,aAAa;YACb,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC;YAC1B,OAAO,EAAE,CAAC,IAAI,CAAC,GAAG,EAAE;gBAClB,MAAM,CAAC,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,CAAC;gBACrB,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;YACnB,CAAC,CAAC,CAAC;QACL,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAEf,iBAAiB,CAAC,MAAM,KAAK,CAAC,IAAI,EAAE,EAAE,EAAE,CAAC,CAAC;QAE1C,YAAY;QACZ,kBAAkB;QAClB,kCAAkC;QAClC,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAEtC,MAAM,CAAC,EAAE,EAAE,EAAE,CAAC,GAAG,KAAK,CAAC;QACvB,yBAAyB;QACzB,IAAI,UAAU,GAAG,KAAK,CAAC;QACvB,IAAI,UAAU,GAAG,IAAI,CAAC;QACtB,iBAAiB,CACb,MAAM,EAAE,CAAC,IAAI,EAAE,EACf,MAAM,EAAE,CAAC,MAAM,CAAC,IAAI,EAAE,CAAC,EAAE,UAAU,EAAE,UAAU,CAAC,CAAC,IAAI,EAAE,CAAC,CAAC;QAE7D,yBAAyB;QACzB,UAAU,GAAG,IAAI,CAAC;QAClB,UAAU,GAAG,KAAK,CAAC;QACnB,iBAAiB,CACb,MAAM,EAAE,CAAC,IAAI,EAAE,EACf,MAAM,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,IAAI,EAAE,UAAU,EAAE,UAAU,CAAC,CAAC,IAAI,EAAE,CAAC,CAAC;IAC/D,CAAC,CAAC,CAAC;AACL,CAAC,CAAC,CAAC;AAEH,iBAAiB,CAAC,wBAAwB,EAAE,QAAQ,EAAE,GAAG,EAAE;IACzD,EAAE,CAAC,eAAe,EAAE,KAAK,IAAI,EAAE;QAC7B,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC;QAChC,MAAM,MAAM,GAAG,EAAE,CAAC,MAAM,EAAE,CAAC,UAAU,CAAC;QACtC,MAAM,QAAQ,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;QACxD,MAAM,MAAM,GAAG,QAAQ,CAAC,CAAC,CAAC,CAAC;QAC3B,MAAM,CAAC,EAAE,CAAC,MAAM,EAAE,CAAC,UAAU,CAAC,CAAC,IAAI,CAAC,MAAM,GAAG,CAAC,CAAC,CAAC;QAChD,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,GAAG,CAAC,CAAC,CAAC;IACpD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,iBAAiB,EAAE,KAAK,IAAI,EAAE;QAC/B,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QACvB,MAAM,QAAQ,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,MAAM,EAAE,CAAC,CAAC,CAAC;QACnD,MAAM,MAAM,GAAG,QAAQ,CAAC,CAAC,CAAC,CAAC;QAC3B,iCAAiC;QACjC,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;IAC9C,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,iBAAiB,EAAE,KAAK,IAAI,EAAE;QAC/B,MAAM,KAAK,GAAG,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC;QAC7C,MAAM,UAAU,GAAG,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;QAChD,MAAM,MAAM,GAAG,UAAU,CAAC,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;QACnD,iBAAiB,CAAC,MAAM,MAAM,CAAC,CAAC,CAAC,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,EAAE,GAAG,CAAC,CAAC,CAAC;IACvD,CAAC,CAAC,CAAC;AACL,CAAC,CAAC,CAAC;AAEH,iBAAiB,CAAC,gBAAgB,EAAE,QAAQ,EAAE,GAAG,EAAE;IACjD,EAAE,CAAC,OAAO,EAAE,KAAK,IAAI,EAAE;QACrB,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QACvB,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QAChC,MAAM,EAAE,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QAExB,MAAM,SAAS,GAAG,EAAE,CAAC,UAAU,CAAC,CAAC,CAAY,EAAE,EAAE;YAC/C,MAAM,KAAK,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC;YAC3B,MAAM,QAAQ,GAAG,CAAC,EAAa,EAAE,EAAE,CAAC,EAAE,CAAC,GAAG,CAAC,EAAE,CAAC,MAAM,CAAC,GAAG,CAAC,CAAC,CAAC;YAC3D,OAAO,EAAC,KAAK,EAAE,QAAQ,EAAC,CAAC;QAC3B,CAAC,CAAC,CAAC;QAEH,MAAM,EAAC,KAAK,EAAE,IAAI,EAAC,GAAG,EAAE,CAAC,YAAY,CAAC,CAAC,CAAC,EAAE,CAAC,SAAS,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC;QAChE,MAAM,CAAC,KAAK,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QACrC,iBAAiB,CAAC,MAAM,KAAK,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;QAC3C,MAAM,CAAC,IAAI,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QACpC,iBAAiB,CAAC,MAAM,IAAI,CAAC,IAAI,EAAE,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC;IAC7C,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,gDAAgD,EAAE,KAAK,IAAI,EAAE;QAC9D,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QACvB,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,EAAE,OAAO,CAAC,CAAC;QAEhC,MAAM,EAAE,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QAExB,MAAM,SAAS,GAAG,EAAE,CAAC,UAAU,CAAC,CAAC,CAAY,EAAE,IAAqB,EAAE,EAAE;YACtE,MAAM,KAAK,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC;YAC3B,IAAI,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;YACV,MAAM,QAAQ,GAAG,CAAC,EAAa,EAAE,KAAe,EAAE,EAAE;gBAClD,MAAM,CAAC,CAAC,CAAC,GAAG,KAAK,CAAC;gBAClB,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;YACnB,CAAC,CAAC;YACF,OAAO,EAAC,KAAK,EAAE,QAAQ,EAAC,CAAC;QAC3B,CAAC,CAAC,CAAC;QAEH,MAAM,GAAG,GAAG,EAAE,CAAC,IAAI,CAAC,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,SAAS,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC;QACvD,MAAM,CAAC,GAAG,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QAEnC,yCAAyC;QACzC,iBAAiB,CAAC,MAAM,GAAG,CAAC,IAAI,EAAE,EAAE,MAAM,EAAE,CAAC,IAAI,EAAE,CAAC,CAAC;IACvD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,2CAA2C,EAAE,KAAK,IAAI,EAAE;QACzD,MAAM,QAAQ,GAAG,EAAE,CAAC,UAAU,CAAC,CAAC,CAAY,EAAE,IAAqB,EAAE,EAAE;YACrE,8DAA8D;YAC9D,IAAI,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;YACV,OAAO;gBACL,KAAK,EAAE,CAAC,CAAC,MAAM,EAAE;gBACjB,QAAQ,EAAE,CAAC,EAAE,EAAE,KAAe,EAAE,EAAE;oBAChC,MAAM,CAAC,CAAC,CAAC,GAAG,KAAK,CAAC;oBAClB,OAAO,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,GAAG,EAAE,CAAC,CAAC;gBACzB,CAAC;aACF,CAAC;QACJ,CAAC,CAAC,CAAC;QACH,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACnC,MAAM,IAAI,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,CAAC,CAAC;QAEvC,iBAAiB,CAAC,MAAM,IAAI,CAAC,CAAC,CAAC,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACnD,iBAAiB,CAAC,MAAM,IAAI,CAAC,CAAC,CAAC,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;IACrD,CAAC,CAAC,CAAC;AACL,CAAC,CAAC,CAAC","sourcesContent":["\n/**\n * @license\n * Copyright 2019 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport {ENGINE} from './engine';\nimport * as tf from './index';\nimport {ALL_ENVS, describeWithFlags} from './jasmine_util';\nimport {Tensor} from './tensor';\nimport {expectArraysClose} from './test_util';\n\ndescribeWithFlags('gradients', ALL_ENVS, () => {\n  it('matmul + relu', async () => {\n    const a = tf.tensor2d([-1, 2, -3, 10, -20, 30], [2, 3]);\n    const b = tf.tensor2d([2, -3, 4, -1, 2, -3], [3, 2]);\n\n    const [da, db] = tf.grads((a: tf.Tensor2D, b: tf.Tensor2D) => {\n      // m = dot(a, b)\n      // y = relu(m)\n      // e = sum(y)\n      const m = tf.matMul(a, b);\n      const y = tf.relu(m);\n      return tf.sum(y);\n    })([a, b]);\n\n    // de/dy = 1\n    // dy/dm = step(m)\n    // de/dm = de/dy * dy/dm = step(m)\n    const dedm = tf.step(tf.matMul(a, b));\n\n    // de/da = dot(de/dy, bT)\n    expect(da.shape).toEqual(a.shape);\n    let transposeA = false;\n    let transposeB = true;\n    expectArraysClose(\n        await da.data(),\n        await tf.matMul(dedm, b, transposeA, transposeB).data());\n\n    // de/db = dot(aT, de/dy)\n    expect(db.shape).toEqual(b.shape);\n    transposeA = true;\n    transposeB = false;\n    expectArraysClose(\n        await db.data(),\n        await tf.matMul(a, dedm, transposeA, transposeB).data());\n  });\n\n  it('grad(f)', async () => {\n    const grad = tf.grad(x => x.square());\n    const result = grad(tf.tensor1d([.1, .2]));\n    expectArraysClose(await result.data(), [.2, .4]);\n  });\n\n  it('calling grad(f) twice works', async () => {\n    const grad = tf.grad(x => x.square());\n\n    const result = grad(tf.tensor1d([.1, .2]));\n    const result2 = grad(tf.tensor1d([.1, .4]));\n    expectArraysClose(await result.data(), [.2, .4]);\n    expectArraysClose(await result2.data(), [.2, .8]);\n  });\n\n  it('grad(f): throwing an error during forward pass', () => {\n    const grad = tf.grad(x => {\n      throw new Error('failed forward pass');\n    });\n    expect(() => grad(tf.zeros([]))).toThrowError();\n    expect(ENGINE.isTapeOn()).toBe(false);\n  });\n\n  it('grad(f): throwing an error during backwards pass', () => {\n    const customOp = tf.customGrad((x: tf.Tensor) => {\n      return {\n        value: x,\n        gradFunc: () => {\n          throw new Error('failed backward pass');\n        }\n      };\n    });\n    const grad = tf.grad(x => customOp(x));\n    expect(() => grad(tf.zeros([]))).toThrowError();\n    expect(ENGINE.isTapeOn()).toBe(false);\n  });\n\n  it('grads(f)', async () => {\n    const grads = tf.grads(x => x.square());\n    const result = grads([tf.tensor1d([.1, .2])]);\n    expectArraysClose(await result[0].data(), [.2, .4]);\n  });\n\n  it('calling grads(f) twice works', async () => {\n    const grads = tf.grads(x => x.square());\n\n    const result = grads([tf.tensor1d([.1, .2])]);\n    const result2 = grads([tf.tensor1d([.1, .4])]);\n    expectArraysClose(await result[0].data(), [.2, .4]);\n    expectArraysClose(await result2[0].data(), [.2, .8]);\n  });\n\n  it('works with reshape', async () => {\n    const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);\n    const exponent = tf.tensor1d([2, 2, 2, 2], 'int32');\n\n    const da = tf.grad(a => {\n      const b = a.flatten();\n      const m = tf.pow(b, exponent);\n      return tf.sum(m);\n    })(a);\n\n    expect(da.shape).toEqual([2, 2]);\n    expectArraysClose(await da.data(), [2, 4, 6, 8]);\n  });\n\n  it('reshape outside tf.grads() throws error', () => {\n    const a = tf.tensor2d([1, 2, 3, 4], [2, 2]);\n    const b = a.flatten();\n    const exponent = tf.tensor1d([2, 2, 2, 2], 'int32');\n\n    const f = () => {\n      tf.grads((a, b) => {\n        const m = tf.pow(b, exponent);\n        return tf.sum(m);\n      })([a, b]);\n    };\n    expect(f).toThrowError();\n  });\n\n  it('does not error if irrelevant (pruned) ops are missing grads',\n     async () => {\n       const a = tf.tensor1d([true, true], 'bool');\n       const b = tf.tensor1d([false, true], 'bool');\n       const da = tf.grad(a => {\n         // Logical has no gradients, but it is irrelevant.\n         a.logicalAnd(b);\n         return a.sum();\n       })(a);\n       expectArraysClose(await da.data(), [1, 1]);\n     });\n\n  it('errors if relevant ops are missing grads', () => {\n    const a = tf.tensor1d([true, true], 'bool');\n    const b = tf.tensor1d([false, true], 'bool');\n    const dfda = tf.grad(a => {\n      // Logical has no gradients, but it's relevant to the output.\n      return a.logicalAnd(b);\n    });\n    expect(() => dfda(a)).toThrowError();\n  });\n\n  it('works with asType', async () => {\n    const a = tf.tensor2d([1, 2, 3, 4], [2, 2], 'int32');\n    const exponent = tf.tensor2d([2, 2, 2, 2], [2, 2], 'int32');\n\n    const da = tf.grad(a => {\n      const b = a.toFloat();\n      const m = tf.pow(b, exponent);\n      return tf.sum(m);\n    })(a);\n\n    expect(da.shape).toEqual([2, 2]);\n    expect(da.dtype).toEqual('float32');\n    expectArraysClose(await da.data(), [2, 4, 6, 8]);\n  });\n\n  it('asType outside of tf.grads() throws error', () => {\n    const a = tf.tensor2d([1, 2, 3, 4], [2, 2], 'int32');\n    const b = a.toFloat();\n    const exponent = tf.tensor2d([2, 2, 2, 2], [2, 2], 'int32');\n\n    const f = () => {\n      tf.grad(a => {\n        const m = tf.pow(b, exponent);\n        return tf.sum(m);\n      })(a);\n    };\n    expect(f).toThrowError();\n  });\n\n  it('saves tensors from the forward pass as expected', () => {\n    const x = tf.scalar(1).variable();\n    const optimizer = tf.train.sgd(0.1);\n    optimizer.minimize(() => {\n      const y = x.square();\n      const z = y.square();\n      y.dispose();\n      return z;\n    });\n  });\n\n  it('custom ops do not leak', () => {\n    const before = tf.memory().numTensors;\n    const x = tf.softmax([1, 2, 3, 4]);\n    x.dispose();\n    const now = tf.memory().numTensors;\n    expect(now).toBe(before);\n  });\n});\n\ndescribeWithFlags('valueAndGradients', ALL_ENVS, () => {\n  it('matmul + relu', async () => {\n    const a = tf.tensor2d([-1, 2, -3, 10, -20, 30], [2, 3]);\n    const b = tf.tensor2d([2, -3, 4, -1, 2, -3], [3, 2]);\n\n    const {value, grads} =\n        tf.valueAndGrads((a: tf.Tensor2D, b: tf.Tensor2D) => {\n          // m = dot(a, b)\n          // y = relu(m)\n          // e = sum(y)\n          const m = tf.matMul(a, b);\n          const y = tf.relu(m);\n          return tf.sum(y);\n        })([a, b]);\n\n    expectArraysClose(await value.data(), 10);\n\n    // de/dy = 1\n    // dy/dm = step(m)\n    // de/dm = de/dy * dy/dm = step(m)\n    const dedm = tf.step(tf.matMul(a, b));\n\n    const [da, db] = grads;\n    // de/da = dot(de/dy, bT)\n    let transposeA = false;\n    let transposeB = true;\n    expectArraysClose(\n        await da.data(),\n        await tf.matMul(dedm, b, transposeA, transposeB).data());\n\n    // de/db = dot(aT, de/dy)\n    transposeA = true;\n    transposeB = false;\n    expectArraysClose(\n        await db.data(),\n        await tf.matMul(a, dedm, transposeA, transposeB).data());\n  });\n\n  it('matmul + relu + inner tidy', async () => {\n    const a = tf.tensor2d([-1, 2, -3, 10, -20, 30], [2, 3]);\n    const b = tf.tensor2d([2, -3, 4, -1, 2, -3], [3, 2]);\n\n    const {value, grads} =\n        tf.valueAndGrads((a: tf.Tensor2D, b: tf.Tensor2D) => {\n          // m = dot(a, b)\n          // y = relu(m)\n          // e = sum(y)\n          const m = tf.matMul(a, b);\n          return tf.tidy(() => {\n            const y = tf.relu(m);\n            return tf.sum(y);\n          });\n        })([a, b]);\n\n    expectArraysClose(await value.data(), 10);\n\n    // de/dy = 1\n    // dy/dm = step(m)\n    // de/dm = de/dy * dy/dm = step(m)\n    const dedm = tf.step(tf.matMul(a, b));\n\n    const [da, db] = grads;\n    // de/da = dot(de/dy, bT)\n    let transposeA = false;\n    let transposeB = true;\n    expectArraysClose(\n        await da.data(),\n        await tf.matMul(dedm, b, transposeA, transposeB).data());\n\n    // de/db = dot(aT, de/dy)\n    transposeA = true;\n    transposeB = false;\n    expectArraysClose(\n        await db.data(),\n        await tf.matMul(a, dedm, transposeA, transposeB).data());\n  });\n});\n\ndescribeWithFlags('higher-order gradients', ALL_ENVS, () => {\n  it('grad(grad(f))', async () => {\n    const x = tf.tensor1d([.1, .2]);\n    const before = tf.memory().numTensors;\n    const gradgrad = tf.grad(tf.grad(x => x.mul(x).mul(x)));\n    const result = gradgrad(x);\n    expect(tf.memory().numTensors).toBe(before + 1);\n    expectArraysClose(await result.data(), [.6, 1.2]);\n  });\n\n  it('grad(grad(x^2))', async () => {\n    const x = tf.scalar(3);\n    const gradgrad = tf.grad(tf.grad(x => x.square()));\n    const result = gradgrad(x);\n    // grad(grad(x^2)) = grad(2x) = 2\n    expectArraysClose(await result.data(), [2]);\n  });\n\n  it('grads(grads(f))', async () => {\n    const grads = tf.grads(x => x.mul(x).mul(x));\n    const gradsgrads = tf.grads(x => grads([x])[0]);\n    const result = gradsgrads([tf.tensor1d([.1, .2])]);\n    expectArraysClose(await result[0].data(), [.6, 1.2]);\n  });\n});\n\ndescribeWithFlags('customGradient', ALL_ENVS, () => {\n  it('basic', async () => {\n    const a = tf.scalar(3);\n    const b = tf.scalar(2, 'int32');\n    const dy = tf.scalar(4);\n\n    const customPow = tf.customGrad((a: tf.Tensor) => {\n      const value = tf.pow(a, b);\n      const gradFunc = (dy: tf.Tensor) => dy.mul(tf.scalar(0.1));\n      return {value, gradFunc};\n    });\n\n    const {value, grad} = tf.valueAndGrad(a => customPow(a))(a, dy);\n    expect(value.shape).toEqual(a.shape);\n    expectArraysClose(await value.data(), [9]);\n    expect(grad.shape).toEqual(a.shape);\n    expectArraysClose(await grad.data(), [.4]);\n  });\n\n  it('second order derivative through customGradient', async () => {\n    const a = tf.scalar(3);\n    const b = tf.scalar(2, 'int32');\n\n    const dy = tf.scalar(5);\n\n    const customPow = tf.customGrad((a: tf.Tensor, save: tf.GradSaveFunc) => {\n      const value = tf.pow(a, b);\n      save([a]);\n      const gradFunc = (dy: tf.Tensor, saved: Tensor[]) => {\n        const [a] = saved;\n        return dy.mul(a);\n      };\n      return {value, gradFunc};\n    });\n\n    const dda = tf.grad(tf.grad(a => customPow(a)))(a, dy);\n    expect(dda.shape).toEqual(a.shape);\n\n    // First order: dy * a. Second order: dy.\n    expectArraysClose(await dda.data(), await dy.data());\n  });\n\n  it('calling gradient of custom op twice works', async () => {\n    const customOp = tf.customGrad((x: tf.Tensor, save: tf.GradSaveFunc) => {\n      // Override gradient of our custom x ^ 2 op to be dy * abs(x);\n      save([x]);\n      return {\n        value: x.square(),\n        gradFunc: (dy, saved: Tensor[]) => {\n          const [x] = saved;\n          return dy.mul(x.abs());\n        }\n      };\n    });\n    const x = tf.tensor1d([-1, -2, 3]);\n    const grad = tf.grad(x => customOp(x));\n\n    expectArraysClose(await grad(x).data(), [1, 2, 3]);\n    expectArraysClose(await grad(x).data(), [1, 2, 3]);\n  });\n});\n"]}