Download lean/OAI/Probability/InvariantIsing/Core/LogMeanLoss.lean from roseking/openAI-math-dataset: direct link, hf CLI and curl.
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2.38 kB
| import OAI.Probability.InvariantIsing.Magnetic.RestrictedFieldOrder | |
| import Mathlib.Analysis.Convex.Integral | |
| namespace OAI | |
| /-! One Gaussian backward step propagates a terminal loss by expectation | |
| under its canonical tilted transition. No lower bound on its positive | |
| exponent is required. -/ | |
| noncomputable section | |
| open MeasureTheory ProbabilityTheory IsingPerceptron | |
| namespace InvariantIsing | |
| lemma integral_le_log_integral_exp {X : Type*} [MeasurableSpace X] | |
| (μ : Measure X) [IsProbabilityMeasure μ] (F : X → ℝ) | |
| (hF : Integrable F μ) (he : Integrable (fun x => Real.exp (F x)) μ) : | |
| (∫ x, F x ∂μ) ≤ Real.log (∫ x, Real.exp (F x) ∂μ) := by | |
| have hj := convexOn_exp.map_integral_le Real.continuous_exp.continuousOn | |
| isClosed_univ (ae_of_all μ (fun _ => Set.mem_univ _)) hF he | |
| have hl := Real.log_le_log (Real.exp_pos (∫ x, F x ∂μ)) hj | |
| rwa [Real.log_exp] at hl | |
| theorem logMean_loss_le_tilted_mean {X : Type*} [MeasurableSpace X] | |
| (μ : Measure X) [IsProbabilityMeasure μ] (F G : X → ℝ) | |
| {b : ℝ} (hb : 0 < b) | |
| (hF : Integrable (fun x => Real.exp (b * F x)) μ) | |
| (hG : Integrable (fun x => Real.exp (b * G x)) μ) | |
| (hD : Integrable (fun x => F x - G x) (μ.tilted (fun x => b * F x))) : | |
| logMean b μ F - logMean b μ G ≤ | |
| ∫ x, F x - G x ∂μ.tilted (fun x => b * F x) := by | |
| let ν := μ.tilted (fun x => b * F x) | |
| let : IsProbabilityMeasure ν := isProbabilityMeasure_tilted hF | |
| have hE : Integrable (fun x => Real.exp (-b * (F x - G x))) ν := by | |
| apply (integrable_tilted_iff hF _).mpr | |
| convert hG using 1 | |
| funext x | |
| rw [smul_eq_mul, ← Real.exp_add] | |
| congr 1 | |
| ring | |
| have hi := integral_le_log_integral_exp ν (fun x => -b * (F x - G x)) | |
| (hD.const_mul (-b)) hE | |
| have he : (∫ x, Real.exp (-b * (F x - G x)) ∂ν) = | |
| (∫ x, Real.exp (b * G x) ∂μ) / ∫ x, Real.exp (b * F x) ∂μ := by | |
| rw [integral_exp_tilted] | |
| congr 2 | |
| funext x | |
| congr 1 | |
| change b * F x + -b * (F x - G x) = b * G x | |
| ring | |
| rw [integral_const_mul, he, Real.log_div (integral_exp_pos μ G hG).ne' | |
| (integral_exp_pos μ F hF).ne'] at hi | |
| change Real.log (∫ x, Real.exp (b * F x) ∂μ) / b - | |
| Real.log (∫ x, Real.exp (b * G x) ∂μ) / b ≤ _ | |
| rw [← sub_div] | |
| apply (div_le_iff₀ hb).mpr | |
| dsimp only [ν] at hi | |
| linarith | |
| end InvariantIsing | |
| end | |
| end OAI | |