Download lean/OAI/Probability/LogConcave/Dynamics/ProbabilityFlowGrowth.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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6.77 kB
| import Mathlib | |
| import OAI.Probability.LogConcave.Sampling.PairGauge | |
| namespace OAI | |
| section | |
| noncomputable section | |
| namespace LogConcaveSampling | |
| open MeasureTheory ProbabilityTheory | |
| open scoped Classical NNReal | |
| variable {d : ℕ} | |
| lemma probabilityFlow_growth {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) | |
| (x : Point d) {r T : ℝ} (hr : 0≤r) (hr1 : r≤1) | |
| (hl : (lam:ℝ)*r^2≤1/2) (hT : 0≤T) (hT1 : T<1) (z : Point d) : | |
| ‖fullProbabilityFlow hF x hr hl T z‖≤circuitGrowthConstant*(circuitD F x+‖z‖) := by | |
| have hf := probabilityFlow_initial_displacement hF x hr hl z ⟨hT,hT1.le⟩ | |
| have hn := norm_le_norm_sub_add (fullProbabilityFlow hF x hr hl T z) z | |
| rw [field_zero_eq_gradient] at hf | |
| have hD : ‖gradient F x‖≤circuitD F x := le_add_of_nonneg_left (Real.sqrt_nonneg _) | |
| have hd := sqrt_le_circuitD F x | |
| have hc := circuitD_nonneg F x | |
| have h₁ := mul_le_mul_of_nonneg_right hr1 (norm_nonneg (gradient F x)) | |
| have h₂ := mul_le_mul_of_nonneg_right (show (lam:ℝ)*r^2≤1 by linarith) | |
| (show 0≤Real.pi*Real.sqrt d+‖z‖ by positivity) | |
| have hp := mul_le_mul_of_nonneg_left hd Real.pi_pos.le | |
| have hb : r*‖gradient F x‖+((lam:ℝ)*r^2)*(Real.pi*Real.sqrt d+‖z‖)≤ | |
| (Real.pi+1)*(circuitD F x+‖z‖) := by | |
| nlinarith [mul_nonneg Real.pi_pos.le (norm_nonneg z)] | |
| have hh := mul_le_mul_of_nonneg_left hb terminalTransportConstant_pos.le | |
| have hz : ‖z‖≤(Real.pi+1)*(circuitD F x+‖z‖) := by | |
| nlinarith [mul_nonneg Real.pi_pos.le (norm_nonneg z),mul_nonneg Real.pi_pos.le hc] | |
| have hc' : terminalTransportConstant+1≤8*(terminalTransportConstant+1) := by | |
| linarith [terminalTransportConstant_pos] | |
| have hh' := mul_le_mul_of_nonneg_right hc' (show 0≤(Real.pi+1)*(circuitD F x+‖z‖) by positivity) | |
| dsimp [circuitGrowthConstant] | |
| nlinarith | |
| lemma interpolationLaw_norm_sq {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) | |
| (x : Point d) {r T : ℝ} (hr : 0≤r) (hr1 : r≤1) | |
| (hl : (lam:ℝ)*r^2≤1/2) (hT : 0≤T) (hT1 : T<1) : | |
| Integrable (fun z : Point d => ‖z‖^2) (interpolationLaw F x r T) ∧ | |
| (∫z : Point d,‖z‖^2 ∂interpolationLaw F x r T)≤4*circuitGrowthConstant^2*(circuitD F x)^2 := by | |
| have hm := (fullProbabilityFlow_lipschitz hF x hr hl ⟨hT,hT1.le⟩).continuous.measurable | |
| have hg := gaussian_growth_sq_moment (fullProbabilityFlow_lipschitz hF x hr hl ⟨hT,hT1.le⟩).continuous | |
| circuitGrowthConstant_pos.le (circuitD_nonneg F x) | |
| (probabilityFlow_growth hF x hr hr1 hl hT hT1) | |
| rw [←fullProbabilityFlow_interpolation_closed hF x hr hl hT hT1] | |
| refine ⟨(integrable_map_measure (by fun_prop) hm.aemeasurable).mpr hg.1,?_⟩ | |
| rw [integral_map hm.aemeasurable (by fun_prop)] | |
| apply hg.2.trans | |
| have hs := pow_le_pow_left₀ (Real.sqrt_nonneg (d:ℝ)) (sqrt_le_circuitD F x) 2 | |
| rw [Real.sq_sqrt (Nat.cast_nonneg d)] at hs | |
| nlinarith [mul_le_mul_of_nonneg_left hs (sq_nonneg circuitGrowthConstant)] | |
| lemma pairGauge_sq_bound {C : ℝ} (hC : 0≤C) (z : Point d × Point d) : | |
| (pairGauge C z)^2≤4*(1+C)^2+4*‖z.1‖^2+4*‖z.2‖^2 := by | |
| have hp : ‖z‖≤‖z.1‖+‖z.2‖ := by | |
| change max ‖z.1‖ ‖z.2‖≤_ | |
| exact max_le (le_add_of_nonneg_right (norm_nonneg _)) (le_add_of_nonneg_left (norm_nonneg _)) | |
| have hq : 0≤pairGauge C z := by unfold pairGauge; positivity | |
| have hb : pairGauge C z≤1+C+‖z.1‖+‖z.2‖ := by dsimp [pairGauge]; linarith | |
| have hh := pow_le_pow_left₀ hq hb 2 | |
| nlinarith [sq_nonneg (1+C-‖z.1‖-‖z.2‖),sq_nonneg (‖z.1‖-‖z.2‖)] | |
| lemma pairGauge_moment (μ : Measure (Point d)) [IsProbabilityMeasure μ] | |
| (hi : Integrable (fun z : Point d => ‖z‖^2) μ) {C : ℝ} (hC : 0≤C) : | |
| Integrable (fun z => (pairGauge C z)^2) (μ.prod (stdGaussian (Point d))) ∧ | |
| (∫z,(pairGauge C z)^2 ∂μ.prod (stdGaussian (Point d)))≤ | |
| 4*(1+C)^2+4*(∫z,‖z‖^2 ∂μ)+4*d := by | |
| have hj : Integrable (fun z : Point d => ‖z‖^2) (stdGaussian (Point d)) := by | |
| simpa only [id_eq] using (IsGaussian.memLp_two_id (μ:=stdGaussian (Point d))).norm.integrable_sq | |
| have hdom : Integrable (fun z : Point d × Point d => 4*(1+C)^2+4*‖z.1‖^2+4*‖z.2‖^2) | |
| (μ.prod (stdGaussian (Point d))) := ((integrable_const (4*(1+C)^2)).add ((hi.comp_fst (stdGaussian (Point d))).const_mul 4)).add | |
| ((hj.comp_snd μ).const_mul 4) | |
| have hgi : Integrable (fun z => (pairGauge C z)^2) (μ.prod (stdGaussian (Point d))) := by | |
| apply hdom.mono' ((pairGauge_measurable C).pow_const 2).aestronglyMeasurable | |
| exact Filter.Eventually.of_forall (fun z => by simpa only [Real.norm_eq_abs,abs_sq,Pi.add_apply] using pairGauge_sq_bound hC z) | |
| refine ⟨hgi,?_⟩ | |
| apply (integral_mono hgi hdom (pairGauge_sq_bound hC)).trans_eq | |
| have hf : Integrable (fun z : Point d × Point d => 4*‖z.1‖^2) (μ.prod (stdGaussian (Point d))) := (hi.comp_fst _).const_mul _ | |
| have hs : Integrable (fun z : Point d × Point d => 4*‖z.2‖^2) (μ.prod (stdGaussian (Point d))) := (hj.comp_snd _).const_mul _ | |
| have hl : Integrable (fun z : Point d × Point d => 4*(1+C)^2+4*‖z.1‖^2) (μ.prod (stdGaussian (Point d))) := (integrable_const _).add hf | |
| rw [integral_add hl hs,integral_add (integrable_const _) hf,integral_const,probReal_univ,one_smul, | |
| integral_const_mul,integral_const_mul] | |
| rw [integral_fun_fst (fun z : Point d => ‖z‖^2),integral_fun_snd (fun z : Point d => ‖z‖^2)] | |
| simp only [probReal_univ,one_smul,stdGaussian_sq_norm] | |
| lemma pairGauge_interpolation_moment {F : Point d → ℝ} {lam : ℝ≥0} (hF : Primitive F lam) | |
| (x : Point d) {r T : ℝ} (hr : 0≤r) (hr1 : r≤1) | |
| (hl : (lam:ℝ)*r^2≤1/2) (hT : 0≤T) (hT1 : T<1) (hd : 1≤d) : | |
| Integrable (fun z => (pairGauge (circuitD F x) z)^2) | |
| ((interpolationLaw F x r T).prod (stdGaussian (Point d))) ∧ | |
| (∫z,(pairGauge (circuitD F x) z)^2 ∂(interpolationLaw F x r T).prod (stdGaussian (Point d)))≤ | |
| (20+16*circuitGrowthConstant^2)*(circuitD F x)^2 := by | |
| let := interpolationLaw_probability hF x hr (by linarith only [hl]) T | |
| have hm := interpolationLaw_norm_sq hF x hr hr1 hl hT hT1 | |
| have hg := pairGauge_moment _ hm.1 (circuitD_nonneg F x) | |
| refine ⟨hg.1,hg.2.trans ?_⟩ | |
| have hs : (1:ℝ)≤Real.sqrt d := by | |
| exact (by norm_num : (1:ℝ)=Real.sqrt 1).trans_le (Real.sqrt_le_sqrt (by exact_mod_cast hd)) | |
| have hD := hs.trans (sqrt_le_circuitD F x) | |
| have hd2 := pow_le_pow_left₀ (Real.sqrt_nonneg (d:ℝ)) (sqrt_le_circuitD F x) 2 | |
| rw [Real.sq_sqrt (Nat.cast_nonneg d)] at hd2 | |
| have hs2 := pow_le_pow_left₀ (show 0≤1+circuitD F x by positivity [circuitD_nonneg F x]) | |
| (show 1+circuitD F x≤2*circuitD F x by linarith) 2 | |
| nlinarith [hm.2] | |
| end LogConcaveSampling | |
| end | |
| end | |
| end OAI | |